docs/cli.md

CLI Guide

The ARIA platform includes a first-party command-line interface (repo-intel) built using Typer.

The CLI communicates directly with the FastAPI server via HTTP and does not replicate database or LLM service bindings locally, keeping execution lightweight.

Installation

Ensure your virtual environment is active, then install the package in editable mode to register the console script:

pip install -e .

---

Commands

1. repo-intel version

Prints the CLI version and queries the status of the remote API.

repo-intel version

2. repo-intel health

Performs connection and subsystem health checks (database, cache, vector store, etc.).

repo-intel health --url http://localhost:8001

3. repo-intel analyze

Triggers full or incremental analysis of a GitHub repository and streams progress updates.

repo-intel analyze https://github.com/fastapi/fastapi --branch master --url http://localhost:8001

4. repo-intel graph

Retrieves React-Flow compatible module dependency structure logs for the specified repository.

repo-intel graph fastapi fastapi

5. repo-intel call-graph

Queries call hierarchy indexes for the specified repository.

repo-intel call-graph fastapi fastapi

6. repo-intel api-surface

Retrieves API surface descriptions, visibility summaries, and exported classifications.

repo-intel api-surface fastapi fastapi

7. repo-intel report

Generates and downloads the Repository Intelligence Report for a given repository.

# Generate and download default HTML report
repo-intel report fastapi/fastapi

# Generate and download Markdown report
repo-intel report fastapi/fastapi --markdown

# Generate and download PDF-friendly HTML report to a specific path
repo-intel report fastapi/fastapi --pdf -o reports/fastapi_audit.html

8. repo-intel mcp

Launches the Model Context Protocol (MCP) server over stdio transport.

repo-intel mcp

---

Model Context Protocol (MCP) Integration

Exposing ARIA as an MCP server allows external LLM clients (such as Claude Desktop or Cursor) to query symbol indexes, call graphs, and run search queries directly.

Claude Desktop Configuration

To register ARIA with Claude Desktop, add the following to your claude_desktop_config.json (typically located at %APPDATA%\Claude\claude_desktop_config.json on Windows or ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

Using Gemini (default provider):

{
  "mcpServers": {
    "repo-intelligence": {
      "command": "repo-intel",
      "args": ["mcp"],
      "env": {
        "GITHUB_TOKEN": "your_github_token_here",
        "LLM_PROVIDER": "gemini",
        "GEMINI_API_KEY": "your_google_ai_studio_key"
      }
    }
  }
}

Using DeepSeek via NVIDIA NIM:

{
  "mcpServers": {
    "repo-intelligence": {
      "command": "repo-intel",
      "args": ["mcp"],
      "env": {
        "GITHUB_TOKEN": "your_github_token_here",
        "LLM_PROVIDER": "deepseek",
        "DEEPSEEK_API_KEY": "your_nvidia_nim_key"
      }
    }
  }
}

If you prefer to run the CLI directly via Python rather than the global executable, use:

{
  "mcpServers": {
    "repo-intelligence": {
      "command": "python",
      "args": ["-m", "backend.cli", "mcp"],
      "env": {
        "GITHUB_TOKEN": "your_github_token_here",
        "LLM_PROVIDER": "gemini",
        "GEMINI_API_KEY": "your_google_ai_studio_key"
      }
    }
  }
}

Ensure the Python executable used is in the virtual environment where repo-intelligence-agent is installed (e.g. C:\path\to\project\.venv\Scripts\python.exe on Windows).