🚧 Documentation In Progress
This documentation is being actively developed. More details will be added soon.
Before installing MCP Codebase Insight, ensure you have the following:
- Python 3.11 or higher
- pip (Python package installer)
- Git
- Docker (optional, for containerized deployment)
- 4GB RAM minimum (8GB recommended)
- 2GB free disk space
- Linux (Ubuntu 20.04+, CentOS 8+)
- macOS (10.15+)
- Windows 10/11 with WSL2
- FastAPI
- Pydantic
- httpx
- sentence-transformers
- qdrant-client
# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install MCP Codebase Insight
pip install mcp-codebase-insight
# Verify installation
mcp-codebase-insight --version
# Pull the Docker image
docker pull modelcontextprotocol/mcp-codebase-insight
# Create necessary directories
mkdir -p docs knowledge cache
# Run the container
docker run -p 3000:3000 \
--env-file .env \
-v $(pwd)/docs:/app/docs \
-v $(pwd)/knowledge:/app/knowledge \
-v $(pwd)/cache:/app/cache \
modelcontextprotocol/mcp-codebase-insight
# Clone the repository
git clone https://github.com/modelcontextprotocol/mcp-codebase-insight.git
cd mcp-codebase-insight
# Create and activate virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Install in development mode
pip install -e .
- Create a
.env
file in your project root:
MCP_HOST=127.0.0.1
MCP_PORT=3000
QDRANT_URL=http://localhost:6333
MCP_DOCS_CACHE_DIR=./docs
MCP_ADR_DIR=./docs/adrs
MCP_KB_STORAGE_DIR=./knowledge
MCP_DISK_CACHE_DIR=./cache
LOG_LEVEL=INFO
- Create required directories:
mkdir -p docs/adrs knowledge cache
-
Vector Database Setup
- Follow the Qdrant Setup Guide to install and configure Qdrant
-
Verify Installation
# Start the server mcp-codebase-insight --host 127.0.0.1 --port 3000 # In another terminal, test the health endpoint curl http://localhost:3000/health
-
Initial Configuration
- Configure authentication (if needed)
- Set up logging
- Configure metrics collection
# Try upgrading pip
pip install --upgrade pip
# Install wheel
pip install wheel
# Retry installation
pip install mcp-codebase-insight
# Check what's using port 3000
lsof -i :3000 # On Linux/macOS
netstat -ano | findstr :3000 # On Windows
# Use a different port
mcp-codebase-insight --port 3001
# Fix directory permissions
chmod -R 755 docs knowledge cache
- Read the Configuration Guide for detailed setup options
- Follow the Quick Start Tutorial to begin using the system
- Check the Best Practices for optimal usage
- Follow the Qdrant Setup to set up the vector database
If you encounter any issues during installation:
- Check the Troubleshooting Guide
- Search existing GitHub Issues
- Open a new issue if needed