AutoDocs MCP Server

AutoDocs MCP Server automatically provides AI assistants with contextual, version-specific documentation for Python project dependencies, eliminating manual package lookup and providing more accurate coding assistance.

Features

Automatic Dependency Scanning: Parse pyproject.toml files and extract dependency information
Version-Specific Caching: Cache documentation based on resolved package versions
Graceful Degradation: Handle malformed dependencies and network issues gracefully
Rich Context: Provide AI assistants with both primary package and dependency documentation
FastMCP Integration: Built with FastMCP for seamless integration with AI tools like Cursor

Installation

# Using uv (recommended)
uv tool install autodocs-mcp

# Using pip
pip install autodocs-mcp

Usage

As an MCP Server

Configure in your Cursor Desktop settings:

{
  "mcpServers": {
    "autodocs-mcp": {
      "command": "uv",
      "args": ["run", "--from", "autodocs-mcp", "autodocs-mcp"],
      "env": {
        "AUTODOCS_CACHE_DIR": "/path/to/cache"
      }
    }
  }
}

Development

# Install dependencies
uv sync --all-extras

# Run tests
uv run pytest

# Run linting
uv run ruff check

# Start development server
uv run hatch run dev

MCP Tools

`scan_dependencies`

Scans project dependencies from pyproject.toml files.

Parameters:

project_path (optional): Path to project directory (defaults to current directory)

Returns:

Project metadata and dependency specifications
Graceful degradation information for malformed dependencies

`get_package_docs` (Coming Soon)

Retrieves formatted documentation for Python packages.

Configuration

Environment variables:

AUTODOCS_CACHE_DIR: Cache directory location (default: ~/.autodocs/cache)
AUTODOCS_MAX_CONCURRENT: Maximum concurrent PyPI requests (default: 10)
AUTODOCS_REQUEST_TIMEOUT: Request timeout in seconds (default: 30)
AUTODOCS_LOG_LEVEL: Logging level (default: INFO)

Architecture

FastMCP Server: Handles MCP protocol communication
Dependency Parser: Parses pyproject.toml with graceful error handling
Documentation Fetcher: Retrieves package info from PyPI (coming soon)
Cache Manager: Version-based caching system (coming soon)

Development Status

This is currently in Priority 1: Core Validation phase:

✅ Basic project setup with hatch/uv
✅ Minimal viable dependency parser
✅ Basic FastMCP integration
✅ scan_dependencies MCP tool
🚧 Testing with real projects

Coming next: Documentation fetching, version-based caching, and rich dependency context.

License

MIT

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Automatically provides AI assistants with contextual, version-specific documentation for Python project dependencies by scanning pyproject.toml files. Eliminates manual package lookup and enables more accurate coding assistance through seamless integration with AI tools.

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