Check Docs - FastMCP Document Indexing Server

A FastMCP server that uses ChromaDB for semantic document indexing and Git diff analysis to identify documentation that needs updates when code changes.

Features

• 📚 Document Indexing: Index markdown documentation with semantic search capabilities
• 🔍 Semantic Search: Search documentation using natural language queries
• 📝 Git Diff Analysis: Automatically identify documentation that needs updates based on code changes
• 🚀 Fast Embeddings: Uses Ollama's nomic-embed-text model for high-quality embeddings
• 💾 Persistent Storage: ChromaDB for reliable vector storage

Prerequisites

1. Python 3.9+
2. uv (Python package manager)

   curl -LsSf https://astral.sh/uv/install.sh | sh
   

3. Ollama with nomic-embed-text model

   # Install Ollama (macOS)
   brew install ollama
   
   # Start Ollama service
   ollama serve
   
   # Pull the embedding model
   ollama pull nomic-embed-text
   

Quick Start

1. Clone and Setup

# Clone the repository
git clone <your-repo-url>
cd check_docs

# Install dependencies with uv
uv sync

# Activate the virtual environment
source .venv/bin/activate  # On macOS/Linux
# or
.venv\Scripts\activate  # On Windows

2. Configure Continue

Create a YAML configuration file at .continue/mcpServers/mcp-server.yaml:

name: Check Docs MCP server
version: 0.0.1
schema: v1
mcpServers:
  - name: check_docs
    command: uv
    args:
      - --directory
      - /path/to/your/check_docs
      - run
      - python
      - server.py

Replace /path/to/your/check_docs with your actual project path.

Usage Examples

Index Documentation

In Continue Agent, ask to index the example docs:

index_docs ./docs # or  path to your docs folder

Search Documentation

Search through indexed documentation:

Search docs for "git integration"

Analyze Code Changes

Check which docs need updates based on code changes:

Check what documentation needs updating based on recent Git changes

Self-Documentation Check

Use the project on itself to ensure all features are documented:

1. First, index the project's own documentation:

   index_docs ./
   

2. Then check if all code features are covered:

   Check docs to see if all features in server.py are covered in the documentation
   

This will analyze the codebase and suggest any missing documentation for new features or tools.

For detailed information about available MCP tools, see available_tools.md.

Development

Running Tests

# Install dev dependencies
uv sync --dev

# Run tests
uv run pytest

Project Structure

check_docs/
├── server.py          # Main FastMCP server implementation
├── pyproject.toml     # Project configuration
├── README.md          # This file
├── example.md         # Implementation guide
├── chroma_db/         # ChromaDB storage (auto-created)
└── example_docs/      # Example documentation (optional)

Environment Variables

• OLLAMA_HOST: Ollama API endpoint (default: http://localhost:11434)
• CHROMA_DB_PATH: ChromaDB storage path (default: ./chroma_db)

Architecture

The server uses:

• FastMCP for the MCP protocol implementation
• ChromaDB for vector storage and similarity search
• Ollama with nomic-embed-text for generating embeddings
• GitPython for repository analysis
• Pydantic for request/response validation

Troubleshooting

Ollama Connection Error

If you see "connection refused" errors:

# Check if Ollama is running
ollama list

# Start Ollama if needed
ollama serve

ChromaDB Persistence

The database is stored in ./chroma_db by default. To reset:

rm -rf chroma_db/

Memory Issues

For large documentation sets, you may need to:

• Increase chunk size to reduce total chunks
• Process files in batches
• Use a cloud ChromaDB instance

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests with uv run pytest
5. Submit a pull request

License

MIT License - see LICENSE file for details