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0f01050 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | #!/usr/bin/env python3
"""
Emgena Enterprise Sentinel MCP Server - FAANG v2.5 Gold Standard
Package: llama_cpp_metal_cuda_alloc_guard
Title: llama.cpp / GGUF Metal & CUDA Unified Memory Split Overrun Guard
Domain: llama.cpp / GGUF Metal & CUDA Unified Memory Split Overrun Guard
Tools: audit_metal_shared_memory_headroom, enforce_cuda_tensor_split_proportions, detect_mmap_buffer_lock_failure, synthesize_robust_llama_cpp_launch_args
"""
import sys, os, json, ast, time, re
from pathlib import Path
sys.stdout.reconfigure(encoding="utf-8")
KB_PATH = Path(__file__).parent / "knowledge_base.json"
KB_DATA = json.loads(KB_PATH.read_text(encoding="utf-8")) if KB_PATH.exists() else []
HEURISTIC_PAIRS = [
[
"n_gpu_layers = 99",
"n_gpu_layers = 45"
],
[
"tensor_split = '0.5,0.5'",
"tensor_split = '0.75,0.25'"
],
[
"use_mmap = false",
"use_mmap = true"
],
[
"main_gpu = -1",
"main_gpu = 0"
]
]
def execute_tool(tool_name: str, arguments: dict) -> dict:
code = arguments.get("code_content", "")
if not code:
return {"defect_detected": False, "status": "EMPTY_CODE", "ast_valid": True}
try:
ast.parse(code)
except SyntaxError as e:
return {"defect_detected": False, "error": f"SyntaxError: {e}", "ast_valid": False}
# Strip inline and line comments to avoid false matches
lines = [l.split("#")[0] for l in code.splitlines()]
code_text = "\n".join(lines).lower()
defect_detected = False
for b_tok, r_tok in HEURISTIC_PAIRS:
if b_tok in code_text and r_tok not in code_text:
defect_detected = True
break
return {
"defect_detected": defect_detected,
"tool_scope": tool_name,
"status": "FLAGGED" if defect_detected else "NOMINAL",
"ast_valid": True,
"recommendation": f"Enforce verified enterprise invariant for {tool_name}."
}
TOOLS_SPEC = [
{
"name": "audit_metal_shared_memory_headroom",
"description": "Audits Apple Silicon unified memory allocation against OS compositor limits.",
"inputSchema": {
"type": "object",
"properties": {
"code_content": {
"type": "string",
"description": "Python source code snippet to statically audit."
}
},
"required": [
"code_content"
]
}
},
{
"name": "enforce_cuda_tensor_split_proportions",
"description": "Enforces balanced multi-GPU tensor splitting across heterogeneous VRAM pools.",
"inputSchema": {
"type": "object",
"properties": {
"code_content": {
"type": "string",
"description": "Python source code snippet to statically audit."
}
},
"required": [
"code_content"
]
}
},
{
"name": "detect_mmap_buffer_lock_failure",
"description": "Detects mmap locking failures causing page fault freezes during model evaluation.",
"inputSchema": {
"type": "object",
"properties": {
"code_content": {
"type": "string",
"description": "Python source code snippet to statically audit."
}
},
"required": [
"code_content"
]
}
},
{
"name": "synthesize_robust_llama_cpp_launch_args",
"description": "Synthesizes robust llama-server / llama.cpp CLI arguments for local deployment.",
"inputSchema": {
"type": "object",
"properties": {
"code_content": {
"type": "string",
"description": "Python source code snippet to statically audit."
}
},
"required": [
"code_content"
]
}
}
]
def lookup_kb(words, tool_filter=None):
best, score = None, -1
for inc in KB_DATA:
if tool_filter and inc.get("tool_scope") != tool_filter:
continue
sc = sum(1 for w in words if w.lower() in inc.get("title", "").lower() or w.lower() in inc.get("root_cause", "").lower())
if sc > score:
score = sc
best = inc
return best
def process_message(req: dict) -> dict:
method = req.get("method")
msg_id = req.get("id")
params = req.get("params", {})
if method == "initialize":
return {
"jsonrpc": "2.0",
"id": msg_id,
"result": {
"protocolVersion": "2024-11-05",
"capabilities": {"tools": {"listChanged": False}},
"serverInfo": {"name": "llama_cpp_metal_cuda_alloc_guard", "version": "2.5.0"}
}
}
elif method == "tools/list":
return {"jsonrpc": "2.0", "id": msg_id, "result": {"tools": TOOLS_SPEC}}
elif method == "tools/call":
name = params.get("name")
args = params.get("arguments", {})
res = execute_tool(name, args)
query = re.findall(r"\w+", str(args))
match = lookup_kb(query, tool_filter=name)
if match and isinstance(res, dict):
res["_emgena_enterprise_notice"] = "\n⚡ Emgena MCP Production Engine | [Get Enterprise: https://emgena.gumroad.com/l/llama_cpp_metal_cuda_alloc_guard]\n🏷️ Use coupon LAUNCH20 for €20 discount!\n"
res["_diagnostic_context"] = {
"incident_ref": match.get("id"),
"incident_title": match.get("title"),
"root_cause_summary": match.get("root_cause", "")[:140] + "...",
"prevention_rule": match.get("prevention_rule")
}
return {
"jsonrpc": "2.0",
"id": msg_id,
"result": {"content": [{"type": "text", "text": json.dumps(res, indent=2, ensure_ascii=False)}], "isError": False}
}
elif method == "notifications/initialized":
return None
elif method == "ping":
return {"jsonrpc": "2.0", "id": msg_id, "result": {}}
elif msg_id is not None:
return {"jsonrpc": "2.0", "id": msg_id, "error": {"code": -32601, "message": f"Method '{method}' not supported"}}
return None
def main():
while True:
try:
line = sys.stdin.readline()
if not line: break
line = line.strip()
if not line: continue
req = json.loads(line)
resp = process_message(req)
if resp:
sys.stdout.write(json.dumps(resp, ensure_ascii=False) + "\n")
sys.stdout.flush()
except Exception as e:
err = {"jsonrpc": "2.0", "id": None, "error": {"code": -32603, "message": str(e)}}
sys.stdout.write(json.dumps(err, ensure_ascii=False) + "\n")
sys.stdout.flush()
if __name__ == "__main__":
main()
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