czty commited on Jul 9

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0d8232c

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1 Parent(s): b7da0d4

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BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.json +1775 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.shard_0_of_4.json +0 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.shard_1_of_4.json +0 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.shard_2_of_4.json +0 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.shard_3_of_4.json +0 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/abundancebin_server.py +134 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/abundancebin_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/requirements.txt +1 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/app/anarci_server.py +183 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/app/anarci_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/app/requirements.txt +1 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/app/bioconductor-alabaster.spatial_server.py +289 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/app/bioconductor-alabaster.spatial_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-annotationhub/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/bioconductor-awaggregator_server.py +214 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/bioconductor-awaggregator_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/requirements.txt +1 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-bsgenome/app/bioconductor-bsgenome_server.py +270 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-bsgenome/app/bioconductor-bsgenome_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/bioconductor-cardspa_server.py +181 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/bioconductor-cardspa_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/requirements.txt +1 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/requirements.txt +2 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/Dockerfile +40 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/app/bioconductor-cellid_server.py +280 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/app/bioconductor-cellid_shim_server.py +45 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/docker-compose.yml +22 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/environment.yaml +10 -0
BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/requirements.txt +2 -0

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/conversion_report.json ADDED Viewed

	@@ -0,0 +1,1775 @@

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+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bin2cell",
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+    "run_help_command": false,
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+    "dockerfile_ready": true
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+  {
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+  {
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+  {
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+    "dockerfile_ready": true
+  },
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+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-blase.manual_bundle.txt",
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+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-cardspa",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cardspa.manual_bundle.txt",
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+  },
+  {
+    "tool_name": "bioconductor-catscradle",
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+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "bioconductor-cdi",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cdi.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
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+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cdi/app/bioconductor-cdi_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-cellhashr",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cellhashr.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
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+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellhashr/app/bioconductor-cellhashr_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-cellid",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cellid.manual_bundle.txt",
+    "run_help_command": false,
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+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-cellmigration",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cellmigration.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellmigration/app/bioconductor-cellmigration_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-clusterfoldsimilarity",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-clusterfoldsimilarity.manual_bundle.txt",
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+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "bioconductor-concordexr",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-concordexr.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-concordexr/app/bioconductor-concordexr_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-cotan",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-cotan.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cotan/app/bioconductor-cotan_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-csoa",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-csoa.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-csoa/app/bioconductor-csoa_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-ctsv",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-ctsv.manual_bundle.txt",
+    "run_help_command": false,
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+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-ctsv/app/bioconductor-ctsv_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-curatedatlasqueryr",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-curatedatlasqueryr.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-curatedatlasqueryr/app/bioconductor-curatedatlasqueryr_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-decontx",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-decontx.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
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+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-decontx/app/bioconductor-decontx_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-deconvobuddies",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-deconvobuddies.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-deconvobuddies/app/bioconductor-deconvobuddies_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-despace",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-despace.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-despace/app/bioconductor-despace_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-dino",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-dino.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-dino/app/bioconductor-dino_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-escher",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/bioconductor-escher.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-escher/app/bioconductor-escher_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "bioconductor-experimentsubset",
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+  {
+    "tool_name": "dropkick",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/dropkick.manual_bundle.txt",
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+    "status": "success",
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+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "easy_vitessce",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/easy_vitessce.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "refine failed (retry=1): Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180) | gemini-2.5-flash: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180)",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "echidna",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/echidna.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_echidna/app/echidna_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "episcanpy",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/episcanpy.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_episcanpy/app/episcanpy_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "flagx",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/flagx.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_flagx/app/flagx_server.py",
+    "dockerfile_ready": true
+  },
+  {
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+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/gene-trajectory-python.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_gene-trajectory-python/app/gene-trajectory-python_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "genecircuitry",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/genecircuitry.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "refine failed (retry=1): Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "htslib",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/htslib.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "refine failed (retry=1): Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "kb-python",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/kb-python.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_kb-python/app/kb-python_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "khipu-metabolomics",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/khipu-metabolomics.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_khipu-metabolomics/app/khipu-metabolomics_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "last",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/last.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_last/app/last_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "liana",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/liana.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "autogenerate_mcp_tool failed: Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180) | gemini-2.5-flash: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180)",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "mameshiba",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/mameshiba.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_mameshiba/app/mameshiba_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "markerrepo",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/markerrepo.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_markerrepo/app/markerrepo_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "mobivision-m",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/mobivision-m.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "autogenerate_mcp_tool failed: Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180) | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "msproteomicstools",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/msproteomicstools.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "autogenerate_mcp_tool failed: Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: exception HTTPSConnectionPool(host='generativelanguage.googleapis.com', port=443): Read timed out. (read timeout=180)",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "multiqc-xenium-extra",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/multiqc-xenium-extra.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_multiqc-xenium-extra/app/multiqc-xenium-extra_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "ngs-smap",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/ngs-smap.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ngs-smap/app/ngs-smap_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "novae",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/novae.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_novae/app/novae_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "openms-thirdparty",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/openms-thirdparty.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_openms-thirdparty/app/openms-thirdparty_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "opticlust",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/opticlust.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "refine failed (retry=1): Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "ourotools",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/ourotools.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "refine failed (retry=1): Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "palantir",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/palantir.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_palantir/app/palantir_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "paste-bio",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/paste-bio.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "skipped_existing",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_paste-bio/app/paste-bio_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "pcdl",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/pcdl.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_pcdl/app/pcdl_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "peakqc",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/peakqc.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_peakqc/app/peakqc_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "peptides",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/peptides.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_peptides/app/peptides_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "piaso",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/piaso.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_piaso/app/piaso_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "pixelator",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/pixelator.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_pixelator/app/pixelator_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "proteomiqon-peptidedb",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/proteomiqon-peptidedb.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_proteomiqon-peptidedb/app/proteomiqon-peptidedb_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "pyrovelocity",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/pyrovelocity.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "failed",
+    "error": "autogenerate_mcp_tool failed: Gemini request failed across all models. gemini-2.5-pro: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-3-flash-preview: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n | gemini-2.5-flash: HTTP 400 - {\n  \"error\": {\n    \"code\": 400,\n    \"message\": \"User location is not supported for the API use.\",\n    \"status\": \"FAILED_PRECONDITION\"\n  }\n}\n",
+    "output_file": "",
+    "dockerfile_ready": false
+  },
+  {
+    "tool_name": "qcatch",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/qcatch.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_qcatch/app/qcatch_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-archr",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-archr.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-archr/app/r-archr_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-azimuth",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-azimuth.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-azimuth/app/r-azimuth_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-beyondcell",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-beyondcell.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-beyondcell/app/r-beyondcell_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-cdseq",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-cdseq.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-cdseq/app/r-cdseq_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-dwls",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-dwls.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-dwls/app/r-dwls_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-epitrace",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-epitrace.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-epitrace/app/r-epitrace_server.py",
+    "dockerfile_ready": true
+  },
+  {
+    "tool_name": "r-flanders",
+    "manual": "/225040511/project/BioScientist/agent_system/toolbase/output/help_docs/manual_bundle_txt/r-flanders.manual_bundle.txt",
+    "run_help_command": false,
+    "status": "success",
+    "error": "",
+    "output_file": "/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_r-flanders/app/r-flanders_server.py",
+    "dockerfile_ready": true
+  },
+  {
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+  {
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+    "dockerfile_ready": true
+  }
+]

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	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install abundancebin via conda (e.g., from bioconda)
+RUN conda install -c bioconda abundancebin -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/abundancebin_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/abundancebin_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/abundancebin_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/abundancebin_server.py ADDED Viewed

	@@ -0,0 +1,134 @@

+import subprocess
+import tempfile
+from pathlib import Path
+from typing import Optional, List
+# This is a placeholder for the MCP decorator.
+# In a real MCP environment, this would be imported from the MCP library.
+def tool(*args, **kwargs):
+    def decorator(f):
+        return f
+    return decorator
+mcp = type("mcp", (), {"tool": tool})
+@mcp.tool()
+def abundancebin(
+    input_file: Path,
+    kmer_len: int = 20,
+    output: Optional[Path] = None,
+    exclude: Optional[int] = None,
+    exclude_max: Optional[int] = None,
+    output_fasta: bool = False,
+    bin_num: Optional[int] = None,
+    recursive_classification: bool = False,
+):
+    """
+    Bins sequences based on k-mer composition and abundance.
+    This tool can either classify sequences into a predefined number of bins
+    or use a recursive classification approach.
+    Args:
+        input_file: Path to the input filename.
+        kmer_len: Composition length (k-mer size). Defaults to 20.
+        output: Path to the output file. Defaults to inputfile.log.
+        exclude: Exclude sequences with a count below this value.
+        exclude_max: Exclude sequences with a count above this value.
+        output_fasta: If set, output results in FASTA format.
+        bin_num: The number of bins to classify sequences into.
+        recursive_classification: If set, undergo recursive classification.
+                                  Cannot be used with bin_num.
+    Returns:
+        A dictionary containing the command executed, stdout, stderr, and a list of output files.
+    """
+    # --- Input Validation ---
+    if not input_file.is_file():
+        raise FileNotFoundError(f"Input file not found: {input_file}")
+    if kmer_len <= 0:
+        raise ValueError("kmer_len must be a positive integer.")
+    if exclude is not None and exclude < 0:
+        raise ValueError("The 'exclude' count must be a non-negative integer.")
+    if exclude_max is not None and exclude_max < 0:
+        raise ValueError("The 'exclude_max' count must be a non-negative integer.")
+    if bin_num is not None and bin_num <= 0:
+        raise ValueError("The 'bin_num' must be a positive integer.")
+    if bin_num is not None and recursive_classification:
+        raise ValueError(
+            "Cannot specify both 'bin_num' and 'recursive_classification'. "
+            "Please choose one method for classification."
+        )
+    # --- Command Construction ---
+    cmd = ["abundancebin"]
+    cmd.extend(["-input", str(input_file)])
+    # Handle default output file path
+    if output:
+        output_path = output
+    else:
+        output_path = input_file.with_suffix('.log')
+    cmd.extend(["-output", str(output_path)])
+    cmd.extend(["-kmer_len", str(kmer_len)])
+    if exclude is not None:
+        cmd.extend(["-exclude", str(exclude)])
+    if exclude_max is not None:
+        cmd.extend(["-exclude_max", str(exclude_max)])
+    if output_fasta:
+        cmd.append("-OUTPUT_FASTA")
+    if bin_num is not None:
+        cmd.extend(["-bin_num", str(bin_num)])
+    if recursive_classification:
+        cmd.append("-RECURSIVE_CLASSIFICATION")
+    command_executed = " ".join(cmd)
+    # --- Subprocess Execution ---
+    try:
+        result = subprocess.run(
+            cmd,
+            capture_output=True,
+            text=True,
+            check=True
+        )
+        stdout = result.stdout
+        stderr = result.stderr
+    except FileNotFoundError:
+        return {
+            "command_executed": command_executed,
+            "stdout": "",
+            "stderr": "Error: 'abundancebin' command not found. Make sure it is installed and in your PATH.",
+            "output_files": []
+        }
+    except subprocess.CalledProcessError as e:
+        return {
+            "command_executed": command_executed,
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "output_files": []
+        }
+    # --- Structured Result Return ---
+    output_files = [str(output_path)] if output_path.exists() else []
+    return {
+        "command_executed": command_executed,
+        "stdout": stdout,
+        "stderr": stderr,
+        "output_files": output_files
+    }

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/abundancebin_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/abundancebin_server.py')
+SERVER_NAME = 'biosci_abundancebin'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/app/requirements.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-abundancebin:
+    build: .
+    image: mcp-abundancebin:latest
+    container_name: mcp-abundancebin
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=abundancebin
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - abundancebin
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_abundancebin/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/app/anarci_server.py ADDED Viewed

	@@ -0,0 +1,183 @@

+from pathlib import Path
+import subprocess
+from typing import Optional, List, Union
+@mcp.tool()
+def run_anarci(
+    sequence: Optional[str] = None,
+    input_file: Optional[str] = None,
+    output_file: Optional[str] = None,
+    scheme: str = "imgt",
+    restrict: Optional[str] = None,
+    species: Optional[str] = None,
+    csv: bool = False,
+    ncpu: int = 1,
+    bit_score_threshold: float = 80.0,
+    assign_germline: bool = False,
+    name: Optional[str] = None,
+    verbose: bool = False
+):
+    """
+    ANARCI: Antibody Numbering and Antigen Receptor ClassIfication.
+    Numbers amino-acid sequences of antibody and T-cell receptor variable domains.
+    Args:
+        sequence: A single amino acid sequence to number.
+        input_file: Path to a FASTA file containing sequences to number.
+        output_file: Path to the output file. If not provided, results are printed to stdout.
+        scheme: Numbering scheme to use. Options: 'imgt', 'kabat', 'chothia', 'martin', 'aho'. (Default: 'imgt')
+        restrict: Restrict numbering to specific domain types. Options: 'ig' (immunoglobulins), 'tr' (T-cell receptors).
+        species: Restrict germline search to specific species (e.g., 'human', 'mouse', 'rat', 'rabbit', 'rhesus', 'pig', 'alpaca').
+        csv: If True, output results in CSV format (horizontal). If False, uses plain text (vertical).
+        ncpu: Number of CPUs to use for parallel processing. (Default: 1)
+        bit_score_threshold: HMMER bit score threshold for domain identification. (Default: 80.0)
+        assign_germline: If True, assign germline species and gene information.
+        name: Name to assign to the single sequence (used with 'sequence' parameter).
+        verbose: If True, produce verbose output.
+    """
+    # Input validation
+    if not sequence and not input_file:
+        raise ValueError("Either 'sequence' or 'input_file' must be provided.")
+    if sequence and input_file:
+        raise ValueError("Provide either 'sequence' or 'input_file', not both.")
+    valid_schemes = ["imgt", "kabat", "chothia", "martin", "aho"]
+    if scheme.lower() not in valid_schemes:
+        raise ValueError(f"Invalid scheme '{scheme}'. Must be one of {valid_schemes}")
+    if restrict and restrict.lower() not in ["ig", "tr"]:
+        raise ValueError("Restrict must be either 'ig' or 'tr'.")
+    # Build command
+    # The CLI tool is typically named 'ANARCI' (uppercase)
+    cmd = ["ANARCI"]
+    if sequence:
+        cmd.extend(["--sequence", sequence])
+        if name:
+            cmd.extend(["--name", name])
+    if input_file:
+        input_path = Path(input_file)
+        if not input_path.exists():
+            raise FileNotFoundError(f"Input file not found: {input_file}")
+        cmd.extend(["--input", str(input_path)])
+    if output_file:
+        cmd.extend(["--outfile", output_file])
+    cmd.extend(["--scheme", scheme.lower()])
+    if restrict:
+        cmd.extend(["--restrict", restrict.lower()])
+    if species:
+        cmd.extend(["--species", species.lower()])
+    if csv:
+        cmd.append("--csv")
+    if assign_germline:
+        cmd.append("--assign_germline")
+    if verbose:
+        cmd.append("--verbose")
+    cmd.extend(["--ncpu", str(ncpu)])
+    cmd.extend(["--bit_score_threshold", str(bit_score_threshold)])
+    try:
+        # Execute the tool
+        result = subprocess.run(
+            cmd,
+            capture_output=True,
+            text=True,
+            check=True
+        )
+        output_files = []
+        if output_file:
+            # ANARCI often appends suffixes depending on the format
+            # e.g., .csv or .txt
+            actual_output = Path(output_file)
+            if actual_output.exists():
+                output_files.append(str(actual_output))
+            else:
+                # Check for common suffixes if the exact file isn't found
+                for suffix in [".csv", ".txt"]:
+                    p = Path(f"{output_file}{suffix}")
+                    if p.exists():
+                        output_files.append(str(p))
+        return {
+            "command_executed": " ".join(cmd),
+            "stdout": result.stdout,
+            "stderr": result.stderr,
+            "output_files": output_files
+        }
+    except subprocess.CalledProcessError as e:
+        return {
+            "command_executed": " ".join(cmd),
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "error": f"ANARCI failed with return code {e.returncode}"
+        }
+    except Exception as e:
+        return {
+            "command_executed": " ".join(cmd),
+            "error": str(e)
+        }
+@mcp.tool()
+def list_anarci_species():
+    """
+    Returns a list of species supported by ANARCI for germline alignment.
+    Note: This is an informational tool based on ANARCI's standard database.
+    """
+    # Standard species supported by ANARCI
+    species_list = [
+        "human", "mouse", "rat", "rabbit", "rhesus", "pig", "alpaca",
+        "dog", "chicken", "cow", "horse", "monkey", "macaque"
+    ]
+    return {
+        "supported_species": species_list,
+        "note": "Availability may depend on the specific ANARCI version and installed HMM databases."
+    }
+@mcp.tool()
+def get_anarci_version():
+    """
+    Retrieves the version information for the installed ANARCI tool.
+    """
+    try:
+        # ANARCI doesn't always have a simple --version flag in older versions,
+        # but we can try to run it to see the help header or use pip/conda info.
+        # Most modern versions support --version.
+        result = subprocess.run(
+            ["ANARCI", "--version"],
+            capture_output=True,
+            text=True,
+            check=False
+        )
+        # If --version fails, try to get it from the help output
+        if result.returncode != 0:
+            result = subprocess.run(
+                ["ANARCI", "--help"],
+                capture_output=True,
+                text=True,
+                check=False
+            )
+        return {
+            "stdout": result.stdout,
+            "stderr": result.stderr
+        }
+    except Exception as e:
+        return {
+            "error": f"Could not determine ANARCI version: {str(e)}"
+        }

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/app/anarci_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/app/anarci_server.py')
+SERVER_NAME = 'biosci_anarci'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-anarci:
+    build: .
+    image: mcp-anarci:latest
+    container_name: mcp-anarci
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=anarci
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_anarci/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - anarci
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/Dockerfile ADDED Viewed

	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install ariba via conda (e.g., from bioconda)
+RUN conda install -c bioconda ariba -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/ariba_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/ariba_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/ariba_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/app/requirements.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-ariba:
+    build: .
+    image: mcp-ariba:latest
+    container_name: mcp-ariba
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=ariba
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - ariba
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_ariba/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/Dockerfile ADDED Viewed

	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install bioconductor-alabaster.spatial via conda (e.g., from bioconda)
+RUN conda install -c bioconda bioconductor-alabaster.spatial -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/bioconductor-alabaster.spatial_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/bioconductor-alabaster.spatial_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/bioconductor-alabaster.spatial_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/app/bioconductor-alabaster.spatial_server.py ADDED Viewed

	@@ -0,0 +1,289 @@

+import subprocess
+import tempfile
+import os
+from pathlib import Path
+from typing import Optional, List, Dict, Any
+# No need to import mcp as per instructions.
+def _run_r_script(script_content: str, cwd: Path) -> Dict[str, Any]:
+    """
+    Executes an R script and captures its output.
+    Args:
+        script_content: The R script as a string.
+        cwd: The current working directory for the R script execution.
+    Returns:
+        A dictionary containing execution details, including command, stdout, stderr,
+        and an error message if the script fails.
+    """
+    with tempfile.NamedTemporaryFile(mode="w", suffix=".R", delete=False) as r_script_file:
+        r_script_file.write(script_content)
+        r_script_path = Path(r_script_file.name)
+    command = ["Rscript", str(r_script_path)]
+    stdout = ""
+    stderr = ""
+    try:
+        process = subprocess.run(
+            command,
+            capture_output=True,
+            text=True,
+            check=True,
+            cwd=cwd # Run R script in the specified working directory
+        )
+        stdout = process.stdout
+        stderr = process.stderr
+    except subprocess.CalledProcessError as e:
+        return {
+            "command_executed": " ".join(command),
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "error": f"R script execution failed with exit code {e.returncode}",
+            "output_files": [],
+        }
+    finally:
+        os.remove(r_script_path)
+    return {
+        "command_executed": " ".join(command),
+        "stdout": stdout,
+        "stderr": stderr,
+        "output_files": [], # This will be populated by the calling function
+    }
+@mcp.tool()
+def save_spatial_experiment(
+    input_spatial_experiment_rds: Path,
+    output_directory: Path,
+    precomputed: bool = True,
+    deferred: bool = False,
+    compression_level: Optional[int] = None,
+    compression_filter: Optional[str] = None,
+) -> Dict[str, Any]:
+    """
+    Saves a SpatialExperiment object and its images into file artifacts.
+    This function serializes an R SpatialExperiment object (provided as an RDS file)
+    into a directory structure of file artifacts, offering a portable alternative
+    to direct RDS serialization. The `alabaster.spatial` package handles the
+    conversion and storage of the object and its associated images.
+    Args:
+        input_spatial_experiment_rds: Path to an RDS file containing the SpatialExperiment object.
+                                      This file must exist.
+        output_directory: Path to the directory where the file artifacts will be saved.
+                          This directory will be created if it does not exist.
+        precomputed: Logical, whether to save precomputed results. Defaults to TRUE.
+        deferred: Logical, whether to defer saving of certain components. Defaults to FALSE.
+        compression_level: Integer, compression level for HDF5 files (0-9).
+                           If None, R's default (typically 6) will be used.
+        compression_filter: String, compression filter for HDF5 files (e.g., "gzip", "lzf").
+                            If None, no specific filter is applied.
+    Returns:
+        A dictionary containing execution details, including the command executed,
+        stdout, stderr, and a list of generated output files/directories.
+        Returns an error if input file is not found, output path is invalid,
+        compression_level is out of range, or R script execution fails.
+    """
+    # Input validation
+    if not input_spatial_experiment_rds.is_file():
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Input RDS file not found at '{input_spatial_experiment_rds}'",
+            "output_files": [],
+        }
+    if output_directory.exists() and not output_directory.is_dir():
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Output path '{output_directory}' exists but is not a directory.",
+            "output_files": [],
+        }
+    try:
+        output_directory.mkdir(parents=True, exist_ok=True)
+    except OSError as e:
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Could not create output directory '{output_directory}': {e}",
+            "output_files": [],
+        }
+    if compression_level is not None and not (0 <= compression_level <= 9):
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: 'compression_level' must be an integer between 0 and 9, got {compression_level}",
+            "output_files": [],
+        }
+    # Construct R script
+    r_script_template = """
+    suppressPackageStartupMessages({{
+        library(alabaster.spatial)
+        library(SpatialExperiment)
+        library(S4Vectors)
+        library(alabaster.base)
+        library(rhdf5) # Explicitly load for HDF5 operations
+    }})
+    input_rds_path <- "{input_rds_path}"
+    output_dir_path <- "{output_dir_path}"
+    # Load the SpatialExperiment object
+    if (!file.exists(input_rds_path)) {{
+        stop(paste0("Input RDS file not found: ", input_rds_path))
+    }}
+    se_object <- readRDS(input_rds_path)
+    # Ensure it's a SpatialExperiment object
+    if (!is(se_object, "SpatialExperiment")) {{
+        stop("Loaded object is not a SpatialExperiment object.")
+    }}
+    # Prepare additional arguments for saveObject
+    save_args <- list(
+        x = se_object,
+        path = output_dir_path,
+        precomputed = {precomputed_r},
+        deferred = {deferred_r}
+    )
+    {compression_level_r}
+    {compression_filter_r}
+    # Call saveObject
+    do.call(alabaster.spatial::saveObject, save_args)
+    message(paste0("SpatialExperiment object saved to: ", output_dir_path))
+    """
+    compression_level_r = f"save_args$compression_level <- {compression_level}" if compression_level is not None else ""
+    compression_filter_r = f"save_args$compression_filter <- '{compression_filter}'" if compression_filter is not None else ""
+    r_script_content = r_script_template.format(
+        input_rds_path=input_spatial_experiment_rds.resolve(),
+        output_dir_path=output_directory.resolve(),
+        precomputed_r=str(precomputed).upper(),
+        deferred_r=str(deferred).upper(),
+        compression_level_r=compression_level_r,
+        compression_filter_r=compression_filter_r,
+    )
+    # Execute R script
+    result = _run_r_script(r_script_content, output_directory.parent) # Run in parent dir to allow output_directory creation
+    if "error" in result:
+        return result
+    result["output_files"] = [str(output_directory.resolve())]
+    return result
+@mcp.tool()
+def read_spatial_experiment(
+    input_directory: Path,
+    output_spatial_experiment_rds: Path,
+    metadata_only: bool = False,
+    image_format: Optional[str] = None,
+) -> Dict[str, Any]:
+    """
+    Loads a SpatialExperiment object and its images from file artifacts.
+    This function reconstructs an R SpatialExperiment object from a directory
+    of file artifacts previously saved by `save_spatial_experiment`.
+    Args:
+        input_directory: Path to the directory containing the file artifacts.
+                         This directory must exist and be valid.
+        output_spatial_experiment_rds: Path to the output RDS file where the
+                                       reconstructed SpatialExperiment object will be saved.
+                                       The parent directory will be created if it does not exist.
+        metadata_only: Logical, whether to only load metadata and not the full data.
+                       Defaults to FALSE.
+        image_format: String, desired image format for loading (e.g., "png", "jpeg", "tiff").
+                      If None, images are loaded in their original format.
+    Returns:
+        A dictionary containing execution details, including the command executed,
+        stdout, stderr, and a list of generated output files.
+        Returns an error if input directory is not found, output path is invalid,
+        or R script execution fails.
+    """
+    # Input validation
+    if not input_directory.is_dir():
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Input directory not found at '{input_directory}'",
+            "output_files": [],
+        }
+    if output_spatial_experiment_rds.exists() and not output_spatial_experiment_rds.is_file():
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Output path '{output_spatial_experiment_rds}' exists but is not a file.",
+            "output_files": [],
+        }
+    try:
+        output_spatial_experiment_rds.parent.mkdir(parents=True, exist_ok=True)
+    except OSError as e:
+        return {
+            "command_executed": "",
+            "stdout": "",
+            "stderr": f"Error: Could not create parent directory for output RDS file '{output_spatial_experiment_rds}': {e}",
+            "output_files": [],
+        }
+    # Construct R script
+    r_script_template = """
+    suppressPackageStartupMessages({{
+        library(alabaster.spatial)
+        library(SpatialExperiment)
+        library(S4Vectors)
+        library(alabaster.base)
+        library(rhdf5) # Explicitly load for HDF5 operations
+    }})
+    input_dir_path <- "{input_dir_path}"
+    output_rds_path <- "{output_rds_path}"
+    # Prepare additional arguments for readObject
+    read_args <- list(
+        path = input_dir_path,
+        metadata.only = {metadata_only_r}
+    )
+    {image_format_r}
+    # Call readObject
+    se_object <- do.call(alabaster.spatial::readObject, read_args)
+    # Save the SpatialExperiment object to RDS
+    saveRDS(se_object, file = output_rds_path)
+    message(paste0("SpatialExperiment object loaded from: ", input_dir_path, " and saved to: ", output_rds_path))
+    """
+    image_format_r = f"read_args$image.format <- '{image_format}'" if image_format is not None else ""
+    r_script_content = r_script_template.format(
+        input_dir_path=input_directory.resolve(),
+        output_rds_path=output_spatial_experiment_rds.resolve(),
+        metadata_only_r=str(metadata_only).upper(),
+        image_format_r=image_format_r,
+    )
+    # Execute R script
+    result = _run_r_script(r_script_content, output_spatial_experiment_rds.parent)
+    if "error" in result:
+        return result
+    result["output_files"] = [str(output_spatial_experiment_rds.resolve())]
+    return result

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/app/bioconductor-alabaster.spatial_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/app/bioconductor-alabaster.spatial_server.py')
+SERVER_NAME = 'biosci_bioconductor_alabaster_spatial'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-bioconductor-alabaster.spatial:
+    build: .
+    image: mcp-bioconductor-alabaster.spatial:latest
+    container_name: mcp-bioconductor-alabaster.spatial
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=bioconductor-alabaster.spatial
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - bioconductor-alabaster.spatial
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-alabaster.spatial/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-annotationhub/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/Dockerfile ADDED Viewed

	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install bioconductor-awaggregator via conda (e.g., from bioconda)
+RUN conda install -c bioconda bioconductor-awaggregator -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/bioconductor-awaggregator_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/bioconductor-awaggregator_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/bioconductor-awaggregator_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/bioconductor-awaggregator_server.py ADDED Viewed

	@@ -0,0 +1,214 @@

+import subprocess
+from pathlib import Path
+from typing import Dict, List
+# MCP decorator is assumed to be available in the execution environment.
+# No import is needed as per the instructions.
+# class mcp:
+#     @staticmethod
+#     def tool():
+#         def decorator(func):
+#             return func
+#         return decorator
+def _run_awaggregator_cli(cmd: List[str], output_map: Dict[str, Path]) -> Dict:
+    """
+    A private helper function to execute the awaggregator wrapper script,
+    handle subprocess execution, and format the output.
+    """
+    command_executed = " ".join(map(str, cmd))
+    try:
+        result = subprocess.run(
+            cmd,
+            capture_output=True,
+            text=True,
+            check=True,
+        )
+        return {
+            "command_executed": command_executed,
+            "stdout": result.stdout,
+            "stderr": result.stderr,
+            "output_files": {key: str(path) for key, path in output_map.items()},
+        }
+    except FileNotFoundError:
+        # This error is raised if 'Rscript' or the wrapper is not in PATH
+        return {
+            "command_executed": command_executed,
+            "stdout": "",
+            "stderr": "Error: 'Rscript' or the wrapper script 'run_awaggregator.R' not found. "
+                      "Please ensure R and the tool's wrapper script are in the system's PATH.",
+            "output_files": {},
+            "error": "Executable not found."
+        }
+    except subprocess.CalledProcessError as e:
+        # This error is raised for non-zero exit codes from the tool
+        return {
+            "command_executed": command_executed,
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "output_files": {},
+            "error": f"Tool execution failed with exit code {e.returncode}",
+        }
+@mcp.tool()
+def aw_weight(
+    expression_matrix: Path,
+    design_matrix: Path,
+    output_weights_file: Path,
+):
+    """
+    Computes adaptive weights for gene expression data meta-analysis.
+    This tool wraps the `aw.weight` function from the Bioconductor `awaggregator` package.
+    It takes an expression data matrix and a design matrix to compute weights for each study.
+    The resulting weights matrix can be used with the `aw_mean` or `aw_median` tools.
+    Args:
+        expression_matrix: Path to the input expression data matrix file (e.g., CSV, TSV).
+                           Rows should represent genes and columns should represent samples.
+        design_matrix: Path to the input design matrix file (e.g., CSV, TSV).
+                       This matrix describes the experimental design.
+        output_weights_file: Path to save the computed weights matrix.
+    Returns:
+        A dictionary containing the execution command, stdout, stderr, and a
+        path to the output weights file.
+    """
+    # --- Input Validation ---
+    if not expression_matrix.is_file():
+        raise FileNotFoundError(f"Input expression matrix file not found: {expression_matrix}")
+    if not design_matrix.is_file():
+        raise FileNotFoundError(f"Input design matrix file not found: {design_matrix}")
+    output_dir = output_weights_file.parent
+    if not output_dir.is_dir():
+        raise NotADirectoryError(f"Output directory does not exist: {output_dir}")
+    # --- Command Construction ---
+    # Assumes a wrapper script 'run_awaggregator.R' is available that handles CLI parsing.
+    cmd = [
+        "Rscript",
+        "run_awaggregator.R",
+        "--method",
+        "weight",
+        "--expression",
+        expression_matrix,
+        "--design",
+        design_matrix,
+        "--output",
+        output_weights_file,
+    ]
+    return _run_awaggregator_cli(cmd, {"weights_matrix": output_weights_file})
+@mcp.tool()
+def aw_mean(
+    data_matrix: Path,
+    weights_matrix: Path,
+    output_file: Path,
+    na_rm: bool = False,
+):
+    """
+    Performs adaptive-weighted mean aggregation on gene expression data.
+    This tool wraps the `aw.mean` function from the Bioconductor `awaggregator` package.
+    It takes a data matrix and a corresponding weights matrix to compute the weighted mean
+    for each gene (row) across studies (columns).
+    Args:
+        data_matrix: Path to the input data matrix file (e.g., CSV, TSV).
+                     Rows should represent genes and columns should represent studies.
+        weights_matrix: Path to the input weights matrix file (e.g., CSV, TSV).
+                        Must have the same dimensions as the data matrix.
+        output_file: Path to save the aggregated results.
+        na_rm: If True, NA values will be removed before computation. Defaults to False.
+    Returns:
+        A dictionary containing the execution command, stdout, stderr, and a
+        path to the output file.
+    """
+    # --- Input Validation ---
+    if not data_matrix.is_file():
+        raise FileNotFoundError(f"Input data matrix file not found: {data_matrix}")
+    if not weights_matrix.is_file():
+        raise FileNotFoundError(f"Input weights matrix file not found: {weights_matrix}")
+    output_dir = output_file.parent
+    if not output_dir.is_dir():
+        raise NotADirectoryError(f"Output directory does not exist: {output_dir}")
+    # --- Command Construction ---
+    cmd = [
+        "Rscript",
+        "run_awaggregator.R",
+        "--method",
+        "mean",
+        "--data",
+        data_matrix,
+        "--weights",
+        weights_matrix,
+        "--output",
+        output_file,
+    ]
+    if na_rm:
+        cmd.append("--na-rm")
+    return _run_awaggregator_cli(cmd, {"aggregated_data": output_file})
+@mcp.tool()
+def aw_median(
+    data_matrix: Path,
+    weights_matrix: Path,
+    output_file: Path,
+    na_rm: bool = False,
+):
+    """
+    Performs adaptive-weighted median aggregation on gene expression data.
+    This tool wraps the `aw.median` function from the Bioconductor `awaggregator` package.
+    It takes a data matrix and a corresponding weights matrix to compute the weighted median
+    for each gene (row) across studies (columns).
+    Args:
+        data_matrix: Path to the input data matrix file (e.g., CSV, TSV).
+                     Rows should represent genes and columns should represent studies.
+        weights_matrix: Path to the input weights matrix file (e.g., CSV, TSV).
+                        Must have the same dimensions as the data matrix.
+        output_file: Path to save the aggregated results.
+        na_rm: If True, NA values will be removed before computation. Defaults to False.
+    Returns:
+        A dictionary containing the execution command, stdout, stderr, and a
+        path to the output file.
+    """
+    # --- Input Validation ---
+    if not data_matrix.is_file():
+        raise FileNotFoundError(f"Input data matrix file not found: {data_matrix}")
+    if not weights_matrix.is_file():
+        raise FileNotFoundError(f"Input weights matrix file not found: {weights_matrix}")
+    output_dir = output_file.parent
+    if not output_dir.is_dir():
+        raise NotADirectoryError(f"Output directory does not exist: {output_dir}")
+    # --- Command Construction ---
+    cmd = [
+        "Rscript",
+        "run_awaggregator.R",
+        "--method",
+        "median",
+        "--data",
+        data_matrix,
+        "--weights",
+        weights_matrix,
+        "--output",
+        output_file,
+    ]
+    if na_rm:
+        cmd.append("--na-rm")
+    return _run_awaggregator_cli(cmd, {"aggregated_data": output_file})

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/bioconductor-awaggregator_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/bioconductor-awaggregator_server.py')
+SERVER_NAME = 'biosci_bioconductor_awaggregator'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/app/requirements.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-bioconductor-awaggregator:
+    build: .
+    image: mcp-bioconductor-awaggregator:latest
+    container_name: mcp-bioconductor-awaggregator
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=bioconductor-awaggregator
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - bioconductor-awaggregator
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-awaggregator/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-bsgenome/app/bioconductor-bsgenome_server.py ADDED Viewed

	@@ -0,0 +1,270 @@

+import subprocess
+from pathlib import Path
+from typing import Optional, List, Dict, Any
+# No need to import mcp as per instructions.
+def _run_r_command(r_code: str) -> Dict[str, Any]:
+    """
+    Executes an R command using Rscript.
+    Args:
+        r_code: The R code string to execute.
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+    """
+    command = ["Rscript", "-e", r_code]
+    try:
+        process = subprocess.run(
+            command,
+            capture_output=True,
+            text=True,
+            check=True
+        )
+        return {
+            "command_executed": " ".join(command),
+            "stdout": process.stdout,
+            "stderr": process.stderr,
+            "output_files": [],
+        }
+    except subprocess.CalledProcessError as e:
+        return {
+            "command_executed": " ".join(command),
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "error": str(e),
+            "output_files": [],
+        }
+    except FileNotFoundError:
+        return {
+            "command_executed": " ".join(command),
+            "stdout": "",
+            "stderr": "Error: Rscript command not found. Please ensure R is installed and in your PATH.",
+            "error": "Rscript not found",
+            "output_files": [],
+        }
+@mcp.tool()
+def install_bsgenome_base_package(
+    bioc_manager_repo: str = "https://bioconductor.org/packages/release/bioc",
+) -> Dict[str, Any]:
+    """
+    Installs the core 'BSgenome' R package and 'BiocManager' if not already present.
+    This function is a prerequisite for using BSgenome data packages or functionalities.
+    It ensures that the necessary R infrastructure is in place.
+    Args:
+        bioc_manager_repo: The Bioconductor repository URL to use for installation.
+                           Defaults to the standard release repository.
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+    """
+    # Input validation
+    if not isinstance(bioc_manager_repo, str) or not bioc_manager_repo:
+        raise ValueError("Bioconductor repository URL must be a non-empty string.")
+    r_code = f"""
+    if (!require("BiocManager", quietly = TRUE)) {{
+        install.packages("BiocManager", repos="https://cloud.r-project.org")
+    }}
+    BiocManager::install("BSgenome", update=FALSE, ask=FALSE, siteRepos="{bioc_manager_repo}")
+    """
+    return _run_r_command(r_code)
+@mcp.tool()
+def install_bsgenome_data_package(
+    data_package_name: str,
+    bioc_manager_repo: str = "https://bioconductor.org/packages/release/bioc",
+) -> Dict[str, Any]:
+    """
+    Installs a specific BSgenome data package (e.g., 'BSgenome.Hsapiens.UCSC.hg38').
+    These data packages contain the actual genome sequences. The core 'BSgenome'
+    package must be installed first using `install_bsgenome_base_package`.
+    Args:
+        data_package_name: The exact name of the BSgenome data package to install
+                           (e.g., "BSgenome.Hsapiens.UCSC.hg38").
+        bioc_manager_repo: The Bioconductor repository URL to use for installation.
+                           Defaults to the standard release repository.
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+    """
+    # Input validation
+    if not isinstance(data_package_name, str) or not data_package_name:
+        raise ValueError("Data package name must be a non-empty string.")
+    if not data_package_name.startswith("BSgenome."):
+        raise ValueError(f"Invalid BSgenome data package name: '{data_package_name}'. "
+                         "It should start with 'BSgenome.'.")
+    if not isinstance(bioc_manager_repo, str) or not bioc_manager_repo:
+        raise ValueError("Bioconductor repository URL must be a non-empty string.")
+    r_code = f"""
+    if (!require("BiocManager", quietly = TRUE)) {{
+        install.packages("BiocManager", repos="https://cloud.r-project.org")
+    }}
+    BiocManager::install("{data_package_name}", update=FALSE, ask=FALSE, siteRepos="{bioc_manager_repo}")
+    """
+    return _run_r_command(r_code)
+@mcp.tool()
+def get_genome_sequence(
+    data_package_name: str,
+    seqname: str,
+    start: int,
+    end: int,
+    masked: bool = False,
+    output_file: Optional[Path] = None,
+) -> Dict[str, Any]:
+    """
+    Retrieves a specific genomic sequence from an installed BSgenome data package.
+    The specified BSgenome data package must be installed prior to calling this function
+    using `install_bsgenome_data_package`.
+    Args:
+        data_package_name: The name of the installed BSgenome data package
+                           (e.g., "BSgenome.Hsapiens.UCSC.hg38").
+        seqname: The name of the sequence (e.g., "chr1", "X").
+        start: The 1-based start coordinate of the sequence to retrieve. Must be a positive integer.
+        end: The 1-based end coordinate of the sequence to retrieve. Must be an integer
+             greater than or equal to start.
+        masked: If True, masked regions (e.g., repeats) will be returned as 'N's.
+                If False, the actual sequence will be returned. Defaults to False.
+        output_file: Optional path to a file where the retrieved sequence will be written.
+                     If not provided, the sequence will be returned in stdout.
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+    """
+    # Input validation
+    if not isinstance(data_package_name, str) or not data_package_name:
+        raise ValueError("Data package name must be a non-empty string.")
+    if not data_package_name.startswith("BSgenome."):
+        raise ValueError(f"Invalid BSgenome data package name: '{data_package_name}'. "
+                         "It should start with 'BSgenome.'.")
+    if not isinstance(seqname, str) or not seqname:
+        raise ValueError("Sequence name (seqname) must be a non-empty string.")
+    if not isinstance(start, int) or start <= 0:
+        raise ValueError("Start coordinate must be a positive integer.")
+    if not isinstance(end, int) or end < start:
+        raise ValueError("End coordinate must be an integer greater than or equal to the start coordinate.")
+    if not isinstance(masked, bool):
+        raise ValueError("Masked parameter must be a boolean.")
+    if output_file is not None and not isinstance(output_file, Path):
+        raise ValueError("Output file must be a Path object or None.")
+    # Prepare R code
+    r_masked_val = "TRUE" if masked else "FALSE"
+    if output_file:
+        output_file_path = Path(output_file)
+        # Ensure parent directory exists
+        output_file_path.parent.mkdir(parents=True, exist_ok=True)
+        # Modify R code to write to file
+        r_code = f"""
+        library({data_package_name})
+        genome_obj <- get(data_package_name)
+        seq <- getSeq(genome_obj, "{seqname}", start={start}, end={end}, masked={r_masked_val})
+        writeLines(as.character(seq), con="{output_file_path.resolve()}")
+        """
+        result = _run_r_command(r_code)
+        if "error" not in result:
+            result["output_files"].append(str(output_file_path.resolve()))
+        return result
+    else:
+        r_code = f"""
+        library({data_package_name})
+        genome_obj <- get(data_package_name)
+        seq <- getSeq(genome_obj, "{seqname}", start={start}, end={end}, masked={r_masked_val})
+        cat(as.character(seq))
+        """
+        return _run_r_command(r_code)
+@mcp.tool()
+def list_available_sequences(
+    data_package_name: str,
+) -> Dict[str, Any]:
+    """
+    Lists the available sequence names (e.g., chromosomes) within an installed BSgenome data package.
+    The specified BSgenome data package must be installed prior to calling this function
+    using `install_bsgenome_data_package`.
+    Args:
+        data_package_name: The name of the installed BSgenome data package
+                           (e.g., "BSgenome.Hsapiens.UCSC.hg38").
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+        The stdout will contain a newline-separated list of sequence names.
+    """
+    # Input validation
+    if not isinstance(data_package_name, str) or not data_package_name:
+        raise ValueError("Data package name must be a non-empty string.")
+    if not data_package_name.startswith("BSgenome."):
+        raise ValueError(f"Invalid BSgenome data package name: '{data_package_name}'. "
+                         "It should start with 'BSgenome.'.")
+    r_code = f"""
+    library({data_package_name})
+    genome_obj <- get(data_package_name)
+    cat(seqnames(genome_obj), sep="\\n")
+    """
+    return _run_r_command(r_code)
+@mcp.tool()
+def get_sequence_lengths(
+    data_package_name: str,
+    seqname: Optional[str] = None,
+) -> Dict[str, Any]:
+    """
+    Retrieves the lengths of sequences (e.g., chromosomes) within an installed BSgenome data package.
+    The specified BSgenome data package must be installed prior to calling this function
+    using `install_bsgenome_data_package`.
+    Args:
+        data_package_name: The name of the installed BSgenome data package
+                           (e.g., "BSgenome.Hsapiens.UCSC.hg38").
+        seqname: Optional. If provided, returns the length of only this specific sequence.
+                 If None, returns lengths for all sequences.
+    Returns:
+        A dictionary containing command execution details, stdout, stderr, and any output files.
+        The stdout will contain sequence names and their lengths, typically one per line.
+    """
+    # Input validation
+    if not isinstance(data_package_name, str) or not data_package_name:
+        raise ValueError("Data package name must be a non-empty string.")
+    if not data_package_name.startswith("BSgenome."):
+        raise ValueError(f"Invalid BSgenome data package name: '{data_package_name}'. "
+                         "It should start with 'BSgenome.'.")
+    if seqname is not None and (not isinstance(seqname, str) or not seqname):
+        raise ValueError("Sequence name (seqname) must be a non-empty string if provided.")
+    if seqname:
+        r_code = f"""
+        library({data_package_name})
+        genome_obj <- get(data_package_name)
+        len <- seqlengths(genome_obj)["{seqname}"]
+        if (is.na(len)) {{
+            stop("Sequence '{seqname}' not found in package '{data_package_name}'.")
+        }}
+        cat("{seqname}:", len, "\\n")
+        """
+    else:
+        r_code = f"""
+        library({data_package_name})
+        genome_obj <- get(data_package_name)
+        lengths <- seqlengths(genome_obj)
+        for (i in seq_along(lengths)) {{
+            cat(names(lengths)[i], ": ", lengths[i], "\\n", sep="")
+        }}
+        """
+    return _run_r_command(r_code)

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-bsgenome/app/bioconductor-bsgenome_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-bsgenome/app/bioconductor-bsgenome_server.py')
+SERVER_NAME = 'biosci_bioconductor_bsgenome'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/Dockerfile ADDED Viewed

	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install bioconductor-cardspa via conda (e.g., from bioconda)
+RUN conda install -c bioconda bioconductor-cardspa -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/bioconductor-cardspa_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/bioconductor-cardspa_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/bioconductor-cardspa_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/bioconductor-cardspa_server.py ADDED Viewed

	@@ -0,0 +1,181 @@

+import subprocess
+import tempfile
+from pathlib import Path
+from typing import Dict, List, Literal, Union
+# This is a placeholder for the MCP framework's decorator.
+# The user's environment will provide the actual mcp.tool implementation.
+class Mcp:
+    def tool(self):
+        def decorator(f):
+            return f
+        return decorator
+mcp = Mcp()
+@mcp.tool()
+def cardspa(
+    sce_object: Path,
+    output_path: Path,
+    phenotype_col: str,
+    location_col_1: str = "row",
+    location_col_2: str = "col",
+    method: Literal["Giotto", "SpaGCN", "BayesSpace"] = "Giotto",
+    num_results: int = 10,
+    num_core: int = 1,
+    min_cells: int = 10,
+    min_pairs: int = 10,
+) -> Dict[str, Union[str, List[str], int]]:
+    """
+    Performs spatial analysis on single-cell data using the cardspa R package.
+    This tool wraps the main `cardspa` function, which can utilize different
+    backend methods like Giotto, SpaGCN, or BayesSpace to identify significant
+    co-enrichment of cell types in spatial transcriptomics data.
+    Args:
+        sce_object: Path to the input SingleCellExperiment object in RDS format.
+        output_path: Path to save the output results object in RDS format.
+        phenotype_col: The column name in the SCE object's colData that contains cell type annotations.
+        location_col_1: The column name for the first spatial coordinate (e.g., 'row', 'x').
+        location_col_2: The column name for the second spatial coordinate (e.g., 'col', 'y').
+        method: The computational method to use for the analysis.
+        num_results: The number of top co-enriched cell type pairs to return.
+        num_core: The number of CPU cores to use for parallel processing.
+        min_cells: The minimum number of cells required for a cell type to be included in the analysis.
+        min_pairs: The minimum number of interacting pairs for a result to be considered significant.
+    Returns:
+        A dictionary containing the executed command, stdout, stderr, and a list of output files.
+        In case of an error, it includes an error message and return code.
+    """
+    # --- Input Validation ---
+    if not sce_object.is_file():
+        raise FileNotFoundError(f"Input file not found: {sce_object}")
+    if not output_path.parent.is_dir():
+        try:
+            output_path.parent.mkdir(parents=True, exist_ok=True)
+        except OSError as e:
+            raise NotADirectoryError(
+                f"Output directory does not exist and could not be created: {output_path.parent}"
+            ) from e
+    if num_results <= 0:
+        raise ValueError("num_results must be a positive integer.")
+    if num_core <= 0:
+        raise ValueError("num_core must be a positive integer.")
+    if min_cells <= 0:
+        raise ValueError("min_cells must be a positive integer.")
+    if min_pairs <= 0:
+        raise ValueError("min_pairs must be a positive integer.")
+    # R script to be executed. It includes package installation for portability.
+    r_script_content = """
+    # run_cardspa.R
+    options(warn=-1)
+    suppressPackageStartupMessages({
+        if (!requireNamespace("argparser", quietly = TRUE)) {
+            install.packages("argparser", repos = "http://cran.us.r-project.org", quiet = TRUE)
+        }
+        if (!requireNamespace("BiocManager", quietly = TRUE)) {
+            install.packages("BiocManager", repos = "http://cran.us.r-project.org", quiet = TRUE)
+        }
+        if (!requireNamespace("cardspa", quietly = TRUE)) {
+            BiocManager::install("cardspa", update=FALSE, ask=FALSE, quiet = TRUE)
+        }
+        if (!requireNamespace("SingleCellExperiment", quietly = TRUE)) {
+            BiocManager::install("SingleCellExperiment", update=FALSE, ask=FALSE, quiet = TRUE)
+        }
+        library(argparser)
+        library(cardspa)
+        library(SingleCellExperiment)
+    })
+    p <- arg_parser("Run cardspa analysis")
+    p <- add_argument(p, "--sce_object", help="Path to the input SingleCellExperiment RDS file", type="character")
+    p <- add_argument(p, "--output_path", help="Path to save the output RDS file", type="character")
+    p <- add_argument(p, "--phenotype_col", help="Column name for cell types", type="character")
+    p <- add_argument(p, "--location_col_1", help="First column name for spatial coordinates", default="row", type="character")
+    p <- add_argument(p, "--location_col_2", help="Second column name for spatial coordinates", default="col", type="character")
+    p <- add_argument(p, "--method", help="Method for spatial analysis (Giotto, SpaGCN, BayesSpace)", default="Giotto", type="character")
+    p <- add_argument(p, "--num_results", help="Number of top results to return", default=10, type="integer")
+    p <- add_argument(p, "--num_core", help="Number of cores for parallel processing", default=1, type="integer")
+    p <- add_argument(p, "--min_cells", help="Minimum number of cells for a cell type", default=10, type="integer")
+    p <- add_argument(p, "--min_pairs", help="Minimum number of interacting pairs", default=10, type="integer")
+    argv <- parse_args(p)
+    if (is.na(argv$sce_object) || is.na(argv$output_path) || is.na(argv$phenotype_col)) {
+      stop("Missing required arguments: --sce_object, --output_path, or --phenotype_col", call. = FALSE)
+    }
+    cat("Reading input SCE object from:", argv$sce_object, "\\n")
+    sce <- readRDS(argv$sce_object)
+    cat("Running cardspa analysis with method:", argv$method, "\\n")
+    results <- cardspa(
+        sce_object = sce,
+        location_col = c(argv$location_col_1, argv$location_col_2),
+        phenotype_col = argv$phenotype_col,
+        method = argv$method,
+        num_results = argv$num_results,
+        num_core = argv$num_core,
+        min_cells = argv$min_cells,
+        min_pairs = argv$min_pairs
+    )
+    cat("Saving results to:", argv$output_path, "\\n")
+    saveRDS(results, file = argv$output_path)
+    cat("cardspa analysis complete. Results saved to:", argv$output_path, "\\n")
+    """
+    # --- Subprocess Execution ---
+    with tempfile.NamedTemporaryFile(mode='w', suffix=".R", delete=False) as r_script_file:
+        r_script_file.write(r_script_content)
+        r_script_path = Path(r_script_file.name)
+    cmd = [
+        "Rscript", str(r_script_path),
+        "--sce_object", str(sce_object.resolve()),
+        "--output_path", str(output_path.resolve()),
+        "--phenotype_col", phenotype_col,
+        "--location_col_1", location_col_1,
+        "--location_col_2", location_col_2,
+        "--method", method,
+        "--num_results", str(num_results),
+        "--num_core", str(num_core),
+        "--min_cells", str(min_cells),
+        "--min_pairs", str(min_pairs),
+    ]
+    command_executed = " ".join(cmd)
+    try:
+        result = subprocess.run(
+            cmd,
+            check=True,
+            capture_output=True,
+            text=True,
+            encoding='utf-8'
+        )
+        return {
+            "command_executed": command_executed,
+            "stdout": result.stdout,
+            "stderr": result.stderr,
+            "output_files": [str(output_path.resolve())]
+        }
+    except FileNotFoundError:
+        raise RuntimeError("Rscript command not found. Please ensure R is installed and in your system's PATH.")
+    except subprocess.CalledProcessError as e:
+        return {
+            "command_executed": command_executed,
+            "stdout": e.stdout,
+            "stderr": e.stderr,
+            "error": "cardspa execution failed.",
+            "return_code": e.returncode,
+            "output_files": []
+        }
+    finally:
+        # Ensure temporary script is always removed
+        if r_script_path.exists():
+            r_script_path.unlink()

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/bioconductor-cardspa_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/bioconductor-cardspa_server.py')
+SERVER_NAME = 'biosci_bioconductor_cardspa'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/app/requirements.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-bioconductor-cardspa:
+    build: .
+    image: mcp-bioconductor-cardspa:latest
+    container_name: mcp-bioconductor-cardspa
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=bioconductor-cardspa
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - bioconductor-cardspa
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cardspa/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/Dockerfile ADDED Viewed

	@@ -0,0 +1,40 @@

+FROM python:3.10-slim
+# Install system dependencies
+RUN apt-get update &&     apt-get install -y         default-jre         wget         curl     && apt-get clean     && rm -rf /var/lib/apt/lists/*
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh &&     bash /tmp/miniconda.sh -b -p /opt/conda &&     rm /tmp/miniconda.sh
+# Add conda to PATH
+ENV PATH="/opt/conda/bin:$PATH"
+# Install bioconductor-cellid via conda (e.g., from bioconda)
+RUN conda install -c bioconda bioconductor-cellid -y &&     conda clean -a
+# Install Python dependencies
+RUN pip install uv
+RUN uv pip install --system fastmcp
+# Create app directory
+WORKDIR /app
+# Copy your MCP server
+COPY app/bioconductor-cellid_server.py /app/
+# Create workspace and output directories
+RUN mkdir -p /app/workspace /app/output
+# Make sure the server script is executable
+RUN chmod +x /app/bioconductor-cellid_server.py
+# Expose port for MCP over HTTP (optional)
+EXPOSE 8000
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3     CMD python -c "import sys; sys.exit(0)"
+# Default command runs the MCP server via stdio
+CMD ["python", "/app/bioconductor-cellid_server.py"]

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/app/bioconductor-cellid_server.py ADDED Viewed

	@@ -0,0 +1,280 @@

+import subprocess
+import os
+from pathlib import Path
+from typing import Optional, List, Union
+import tempfile
+def run_r_command(script_content: str):
+    """Helper function to execute R code via Rscript"""
+    with tempfile.NamedTemporaryFile(mode='w', suffix='.R', delete=False) as tmp:
+        tmp.write(script_content)
+        tmp_path = tmp.name
+    try:
+        result = subprocess.run(
+            ["Rscript", tmp_path],
+            capture_output=True,
+            text=True,
+            check=True
+        )
+        return result.stdout, result.stderr
+    except subprocess.CalledProcessError as e:
+        raise RuntimeError(f"R execution failed: {e.stderr}\nStdout: {e.stdout}")
+    finally:
+        if os.path.exists(tmp_path):
+            os.remove(tmp_path)
+@mcp.tool()
+def cellid_run_mca(
+    input_rds: str,
+    output_rds: str,
+    nmcs: int = 50,
+    assay: str = "RNA",
+    slot: str = "counts",
+    features: Optional[List[str]] = None
+):
+    """
+    Performs Multiple Correspondence Analysis (MCA) on a SingleCellExperiment or Seurat object.
+    MCA allows for the simultaneous representation of cells and genes in a common low-dimensional space.
+    """
+    input_path = Path(input_rds)
+    output_path = Path(output_rds)
+    if not input_path.exists():
+        return {"error": f"Input file {input_rds} not found."}
+    if nmcs <= 0:
+        return {"error": "nmcs must be a positive integer."}
+    features_r = "NULL"
+    if features:
+        features_formatted = ", ".join([f"'{f}'" for f in features])
+        features_r = f"c({features_formatted})"
+    r_script = f"""
+    library(CelliD)
+    library(Seurat)
+    library(SingleCellExperiment)
+    obj <- readRDS("{input_path}")
+    # Run MCA
+    obj <- RunMCA(obj, nmcs = {nmcs}, assay = "{assay}", slot = "{slot}", features = {features_r})
+    saveRDS(obj, "{output_path}")
+    """
+    try:
+        stdout, stderr = run_r_command(r_script)
+        return {
+            "command_executed": "RunMCA",
+            "stdout": stdout,
+            "stderr": stderr,
+            "output_files": [str(output_path)]
+        }
+    except Exception as e:
+        return {"error": str(e)}
+@mcp.tool()
+def cellid_get_cell_gene_set(
+    input_rds: str,
+    output_csv: str,
+    dims: int = 50,
+    n_features: int = 200
+):
+    """
+    Extracts the top gene signatures for each individual cell based on MCA coordinates.
+    """
+    input_path = Path(input_rds)
+    output_path = Path(output_csv)
+    if not input_path.exists():
+        return {"error": f"Input file {input_rds} not found."}
+    if dims <= 0 or n_features <= 0:
+        return {"error": "dims and n_features must be positive integers."}
+    r_script = f"""
+    library(CelliD)
+    library(Seurat)
+    library(SingleCellExperiment)
+    library(data.table)
+    obj <- readRDS("{input_path}")
+    # Extract gene sets per cell
+    # dims is treated as 1:dims
+    gene_sets <- GetCellGeneSet(obj, dims = 1:{dims}, n.features = {n_features})
+    # Convert list to a data table for export
+    # Each column is a cell, rows are top genes
+    max_len <- max(sapply(gene_sets, length))
+    dt <- as.data.frame(lapply(gene_sets, function(x) c(x, rep(NA, max_len - length(x)))))
+    write.csv(dt, "{output_path}", row.names = FALSE)
+    """
+    try:
+        stdout, stderr = run_r_command(r_script)
+        return {
+            "command_executed": "GetCellGeneSet",
+            "stdout": stdout,
+            "stderr": stderr,
+            "output_files": [str(output_path)]
+        }
+    except Exception as e:
+        return {"error": str(e)}
+@mcp.tool()
+def cellid_run_cell_hgt(
+    input_rds: str,
+    pathways_gmt: str,
+    output_rds: str,
+    dims: int = 50,
+    n_features: int = 200,
+    min_size: int = 5
+):
+    """
+    Performs cell-type assignment or functional enrichment using a Hypergeometric Test (HGT).
+    Matches per-cell gene signatures against a reference database (GMT format).
+    """
+    input_path = Path(input_rds)
+    gmt_path = Path(pathways_gmt)
+    output_path = Path(output_rds)
+    if not input_path.exists():
+        return {"error": f"Input RDS {input_rds} not found."}
+    if not gmt_path.exists():
+        return {"error": f"GMT file {pathways_gmt} not found."}
+    r_script = f"""
+    library(CelliD)
+    library(Seurat)
+    library(SingleCellExperiment)
+    library(fgsea)
+    obj <- readRDS("{input_path}")
+    pathways <- gmtPathways("{gmt_path}")
+    # Run Hypergeometric Test
+    # Returns a matrix of -log10(p-value)
+    hgt_matrix <- RunCellHGT(obj, pathways = pathways, dims = 1:{dims}, n.features = {n_features}, minSize = {min_size})
+    # If Seurat, we can add it as an assay or metadata
+    if(inherits(obj, "Seurat")) {{
+        obj[["HGT"]] <- CreateAssayObject(counts = hgt_matrix)
+    }} else {{
+        # For SCE, add to altExp
+        altExp(obj, "HGT") <- SummarizedExperiment(assays = list(counts = hgt_matrix))
+    }}
+    saveRDS(obj, "{output_path}")
+    """
+    try:
+        stdout, stderr = run_r_command(r_script)
+        return {
+            "command_executed": "RunCellHGT",
+            "stdout": stdout,
+            "stderr": stderr,
+            "output_files": [str(output_path)]
+        }
+    except Exception as e:
+        return {"error": str(e)}
+@mcp.tool()
+def cellid_run_gsea(
+    input_rds: str,
+    pathways_gmt: str,
+    output_rds: str,
+    dims: int = 50
+):
+    """
+    Performs Gene Set Enrichment Analysis (GSEA) on cells using the MCA gene rankings.
+    """
+    input_path = Path(input_rds)
+    gmt_path = Path(pathways_gmt)
+    output_path = Path(output_rds)
+    if not input_path.exists():
+        return {"error": f"Input RDS {input_rds} not found."}
+    if not gmt_path.exists():
+        return {"error": f"GMT file {pathways_gmt} not found."}
+    r_script = f"""
+    library(CelliD)
+    library(Seurat)
+    library(SingleCellExperiment)
+    library(fgsea)
+    obj <- readRDS("{input_path}")
+    pathways <- gmtPathways("{gmt_path}")
+    # Run GSEA
+    # This calculates enrichment scores for each cell and each pathway
+    gsea_res <- RunGSEA(obj, pathways = pathways, dims = 1:{dims})
+    # Save results (usually returns a matrix of NES)
+    if(inherits(obj, "Seurat")) {{
+        obj[["GSEA"]] <- CreateAssayObject(counts = gsea_res)
+    }} else {{
+        altExp(obj, "GSEA") <- SummarizedExperiment(assays = list(counts = gsea_res))
+    }}
+    saveRDS(obj, "{output_path}")
+    """
+    try:
+        stdout, stderr = run_r_command(r_script)
+        return {
+            "command_executed": "RunGSEA",
+            "stdout": stdout,
+            "stderr": stderr,
+            "output_files": [str(output_path)]
+        }
+    except Exception as e:
+        return {"error": str(e)}
+@mcp.tool()
+def cellid_run_group_mca(
+    input_rds: str,
+    group_by: str,
+    output_rds: str,
+    nmcs: int = 50,
+    assay: str = "RNA",
+    slot: str = "counts"
+):
+    """
+    Performs MCA on grouped cells (e.g., by cluster or cell type) rather than individual cells.
+    Useful for extracting group-specific gene signatures.
+    """
+    input_path = Path(input_rds)
+    output_path = Path(output_rds)
+    if not input_path.exists():
+        return {"error": f"Input file {input_rds} not found."}
+    r_script = f"""
+    library(CelliD)
+    library(Seurat)
+    library(SingleCellExperiment)
+    obj <- readRDS("{input_path}")
+    # Run Group MCA
+    # This aggregates cells by the specified metadata column before MCA
+    group_mca <- RunGroupMCA(obj, group.by = "{group_by}", nmcs = {nmcs}, assay = "{assay}", slot = "{slot}")
+    saveRDS(group_mca, "{output_path}")
+    """
+    try:
+        stdout, stderr = run_r_command(r_script)
+        return {
+            "command_executed": "RunGroupMCA",
+            "stdout": stdout,
+            "stderr": stderr,
+            "output_files": [str(output_path)]
+        }
+    except Exception as e:
+        return {"error": str(e)}

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/app/bioconductor-cellid_shim_server.py ADDED Viewed

	@@ -0,0 +1,45 @@

+#!/usr/bin/env python3
+from __future__ import annotations
+import ast
+from pathlib import Path
+from mcp.server.fastmcp import FastMCP
+SOURCE_SERVER = Path('/225040511/project/BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/app/bioconductor-cellid_server.py')
+SERVER_NAME = 'biosci_bioconductor_cellid'
+class _ShimMCP:
+    @staticmethod
+    def tool():
+        def _decorator(fn):
+            return fn
+        return _decorator
+def _load_functions():
+    code = SOURCE_SERVER.read_text(encoding="utf-8")
+    tree = ast.parse(code, filename=str(SOURCE_SERVER))
+    function_names = [n.name for n in tree.body if isinstance(n, ast.FunctionDef) and not n.name.startswith("_")]
+    namespace = {
+        "__name__": "__mcp_source__",
+        "mcp": _ShimMCP(),
+    }
+    exec(compile(code, str(SOURCE_SERVER), "exec"), namespace, namespace)
+    loaded = []
+    for name in function_names:
+        fn = namespace.get(name)
+        if callable(fn):
+            loaded.append(fn)
+    return loaded
+mcp = FastMCP(SERVER_NAME)
+for _fn in _load_functions():
+    mcp.tool()(_fn)
+if __name__ == "__main__":
+    mcp.run(transport="stdio")

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/docker-compose.yml ADDED Viewed

	@@ -0,0 +1,22 @@

+version: '3.8'
+services:
+  mcp-bioconductor-cellid:
+    build: .
+    image: mcp-bioconductor-cellid:latest
+    container_name: mcp-bioconductor-cellid
+    ports:
+      - "8000:8000"
+    environment:
+      - MCP_SERVER_NAME=bioconductor-cellid
+    volumes:
+      - ./workspace:/app/workspace
+      - ./output:/app/output
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 5s

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/environment.yaml ADDED Viewed

	@@ -0,0 +1,10 @@

+name: mcp-tool
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - bioconductor-cellid
+  - python=3.10

BioScientist/agent_system/toolbase/mcp_batch_from_manual_txt/mcp_bioconductor-cellid/requirements.txt ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ fastmcp
2	+ mcp