๐ AI-powered Python package intelligence - search, analyze, and understand PyPI packages through MCP
Project description
๐ MCP-PyPI
A security-focused Model Context Protocol (MCP) server that helps AI agents write safer Python code. Search packages, scan for vulnerabilities, audit dependencies, and ensure security across your entire Python project.
โจ What is MCP-PyPI?
MCP-PyPI is a security-focused Model Context Protocol server that empowers AI assistants to write safer Python code. Beyond basic package information, it provides comprehensive vulnerability scanning, dependency auditing, and proactive security recommendations to ensure AI-generated code uses secure, up-to-date dependencies.
๐ก๏ธ Security First: Every tool is designed to encourage security best practices, from checking vulnerabilities before suggesting packages to scanning entire project dependency trees for hidden risks.
๐ฏ Key Features
- ๐ก๏ธ Comprehensive Security Scanning - Check vulnerabilities using OSV database across packages, dependencies, and entire projects
- ๐ Security-Aware Package Search - Find safe packages from 500,000+ options with vulnerability status
- ๐ Project-Wide Security Audits - Scan requirements.txt, pyproject.toml, and installed environments
- ๐ Deep Dependency Analysis - Detect vulnerabilities in transitive dependencies others might miss
- ๐จ Proactive Security Alerts - Get warnings before adding vulnerable packages to projects
- ๐ Risk Assessment & Scoring - Security scores, fix time estimates, and prioritized remediation plans
- โก Smart Caching - Fast vulnerability checks with configurable TTL for different data types
- ๐ Version Management - Track releases, compare versions, identify security updates
๐ค Why Security Matters
When AI assistants suggest Python packages, they might unknowingly recommend packages with known vulnerabilities. MCP-PyPI ensures that:
- Before Installation: AI checks for vulnerabilities before suggesting any package
- During Development: Continuous scanning catches new vulnerabilities in existing dependencies
- Before Deployment: Comprehensive audits ensure production code is secure
- Transitive Safety: Hidden vulnerabilities in dependencies-of-dependencies are detected
๐ Quick Start
Installation
# Basic installation
pip install mcp-pypi
# With HTTP transport support
pip install "mcp-pypi[http]"
# With all features
pip install "mcp-pypi[all]"
Running the Server
# Start with default stdio transport (for Claude Desktop)
mcp-pypi serve
# Alternative stdio command (for compatibility)
mcp-pypi stdio
# Start with HTTP transport
mcp-pypi serve --transport http
# With custom cache directory
mcp-pypi serve --cache-dir ~/.pypi-cache
๐ค Using with Claude Desktop
Add to your Claude Desktop configuration (claude.json):
{
"servers": {
"pypi": {
"command": "mcp-pypi",
"args": ["serve"],
"description": "Access Python package information from PyPI"
}
}
}
// Alternative using stdio command (equivalent to above)
{
"servers": {
"pypi": {
"command": "mcp-pypi",
"args": ["stdio"],
"description": "Access Python package information from PyPI"
}
}
}
๐ฅ๏ธ Using with Claude Code (Terminal)
Add the MCP server to Claude Code:
# Add the server (using serve command)
claude mcp add mcp-pypi -- mcp-pypi serve
# Alternative using stdio command
claude mcp add mcp-pypi -- mcp-pypi stdio
# The server will be available in your next Claude Code session
๐ ๏ธ Available Tools
Package Discovery
- search_packages - ๐ Search PyPI to discover Python packages
- get_package_info - ๐ฆ Get comprehensive package details
- check_package_exists - โ Verify if a package exists on PyPI
Version Management
- get_latest_version - ๐ Check the latest available version
- list_package_versions - ๐ List all available versions
- compare_versions - ๐ Compare two package versions
Dependency Analysis
- get_dependencies - ๐ Analyze package dependencies
- get_dependency_tree - ๐ณ Visualize complete dependency tree
- check_vulnerabilities - ๐ก๏ธ Scan for security vulnerabilities using OSV database
- scan_dependency_vulnerabilities - ๐ก๏ธ๐ Deep scan entire dependency tree for vulnerabilities
Project Management
- check_requirements_txt - ๐๐ก๏ธ Security audit requirements.txt files
- check_pyproject_toml - ๐ฏ๐ก๏ธ Security audit pyproject.toml dependencies
- scan_installed_packages - ๐ก๏ธ๐ป Scan virtual/system environments for vulnerabilities
- security_audit_project - ๐ก๏ธ๐๐จ Comprehensive project-wide security audit
Statistics & Info
- get_package_stats - ๐ Get download statistics
- get_package_metadata - ๐ Access complete metadata
- get_package_documentation - ๐ Find documentation links
๐ก Example Usage
Once configured, you can ask Claude:
- "Search for web scraping packages on PyPI"
- "What's the latest version of Django?"
- "Check if my requirements.txt has any outdated packages"
- "Show me the dependencies for FastAPI"
- "Find popular data visualization libraries"
- "Compare pandas version 2.0.0 with 2.1.0"
๐ง Advanced Configuration
Environment Variables
# Custom cache directory
export PYPI_CACHE_DIR=/path/to/cache
# Cache TTL (seconds)
export PYPI_CACHE_TTL=3600
# Vulnerability cache TTL (seconds) - default 1 hour
export PYPI_VULNERABILITY_CACHE_TTL=3600
# Custom user agent
export PYPI_USER_AGENT="MyApp/1.0"
Programmatic Usage
from mcp_pypi.server import PyPIMCPServer
from mcp_pypi.core.models import PyPIClientConfig
# Custom configuration
config = PyPIClientConfig(
cache_dir="/tmp/pypi-cache",
cache_ttl=7200,
cache_strategy="hybrid"
)
# Create and run server
server = PyPIMCPServer(config=config)
server.run(transport="http", host="0.0.0.0", port=8080)
๐ Performance
- Intelligent Caching: Hybrid memory/disk caching with LRU/LFU/FIFO strategies
- Concurrent Requests: Async architecture for parallel operations
- Minimal Overhead: Direct PyPI API integration
- Configurable TTL: Control cache duration based on your needs
๐ก๏ธ Security & Caching
Vulnerability Data Caching
Vulnerability checks are cached to improve performance and reduce API load:
- Default TTL: 1 hour (3600 seconds)
- Configurable: Use
PYPI_VULNERABILITY_CACHE_TTLenvironment variable - Cache Key: Based on package name + version
- OSV API: Queries are cached to avoid repeated lookups
Why Caching Matters
- Performance: Vulnerability checks can be slow, caching makes subsequent checks instant
- Rate Limiting: Prevents hitting OSV API rate limits during large scans
- Consistency: Ensures consistent results during a security audit
- Offline Support: Cached results available even if OSV API is unreachable
Cache Management
# Clear all caches
mcp-pypi cache clear
# View cache statistics
mcp-pypi cache stats
# Set shorter TTL for development (5 minutes)
export PYPI_VULNERABILITY_CACHE_TTL=300
๐ค Contributing
Contributions are welcome! Please check out our Contributing Guide for details.
Development Setup
# Clone the repository
git clone https://github.com/kimasplund/mcp-pypi.git
cd mcp-pypi
# Install in development mode
pip install -e ".[dev]"
# Run tests
pytest
# Run with debug logging
mcp-pypi serve --log-level DEBUG
๐ License
This project is dual-licensed:
- Open Source: MIT License for personal, educational, and non-profit use - see LICENSE
- Commercial: Commercial License required for business use - see LICENSE-COMMERCIAL
Quick License Guide:
- โ Free to use: Personal projects, education, non-profits, open source
- ๐ฐ Commercial license required: For-profit companies, commercial products, consulting
- ๐ง Contact: kim.asplund@gmail.com for commercial licensing
๐ Acknowledgments
- Built on the Model Context Protocol
- Powered by the Python Package Index
- Enhanced with FastMCP
๐ Support
- ๐ง Email: kim.asplund@gmail.com
- ๐ Issues: GitHub Issues
- ๐ฌ Discussions: GitHub Discussions
Made with โค๏ธ for the Python and AI communities
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