🎤 mcpypi 🥧

Your Master of Ceremonies for PyPI

mcpypi (pronounced "MC-py-pie") is your Master of Ceremonies for PyPI! 🎤

The ultimate PyPI package intelligence platform, now available through Model Context Protocol

Just like a world-class DJ or MC controls the music and keeps the party flowing, mcpypi orchestrates your entire Python package ecosystem. It's the perfect fusion of "MCP" + "PyPI" + the Python community's beloved tradition of naming everything with "pie" 🥧 (NumPy, SciPy, SymPy... you get it!).

Think of mcpypi as your intelligent package DJ - it knows all the tracks (packages), their dependencies, security vulnerabilities, licenses, and can help you mix the perfect environment for your Python projects!

🌟 Why mcpypi?

Features

Your MC knows how to drop the beats! 🎵

• 📦 Track Info - Get the full story on any PyPI package (metadata, versions, dependencies)
• 🐍 Compatibility Check - Know which Python versions can handle your tracks
• 🔍 Deep Mixing - Advanced dependency analysis and recursive resolution to avoid conflicts
• 📥 Collection Building - Download packages with all their dependencies for offline mixing
• 📊 Chart Analysis - Real-time download statistics and popularity trends
• 🏆 Top 40 - Discover the hottest packages trending right now
• 🔒 Security Scanning - Keep your playlist safe from vulnerable packages
• 📄 License Mixing - Ensure your package mix is legally compatible
• 🏥 Health Check - Assess package quality across 7 key metrics
• 📋 Setlist Analysis - Parse and analyze requirements files in any format
• 🎯 Smart Prompts - MCP templates for guided decision-making
• 🏢 Private Venues - Support for private PyPI repositories
• ⚡ Live Performance - Fast async operations with intelligent caching
• 🛠️ Universal Mixer - Easy integration with all MCP clients

🚀 Quick Start

Ready to get your MC on the decks? Here's how to book mcpypi for your next Python party! 🎉

Option 1: Lightning Setup ⚡ (Recommended)

# One-liner - Run immediately with uvx
uvx mcpypi

Option 2: Traditional Install 📦

# Install from PyPI
pip install mcpypi

# Run the server  
python -m pypi_query_mcp.server

Option 3: Claude Code Integration 🎤

# Connect directly to Claude Code
claude mcp add mcpypi -- uvx mcpypi

🎭 Live Demo

Here's what your MC can do for you:

"What are the security vulnerabilities 
in Django 4.1?"

"Show me the top 10 trending 
ML packages this week"

"Compare the health scores of 
FastAPI vs Django vs Flask"

"Check if my requirements.txt 
is MIT license compatible"

🛠️ Advanced Installation

git clone https://github.com/rsp2k/pypi-query-mcp-server.git
cd pypi-query-mcp-server
uv sync
uv run pypi-query-mcp

# Build the package
uv run python -m build

# Publish to PyPI (requires ~/.pypirc configuration)
uv run twine upload dist/*

# Publish to TestPyPI
uv run twine upload --repository testpypi dist/*

[distutils]
index-servers = pypi testpypi

[pypi]
username = __token__
password = pypi-your-production-token-here

[testpypi]
repository = https://test.pypi.org/legacy/
username = __token__
password = pypi-your-test-token-here

🎛️ Configuration

🖥️ Claude Desktop

Add to your Claude Desktop configuration file:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "pypi-query": {
      "command": "uvx",
      "args": ["--from", "mcpypi", "mcpypi"],
      "env": {
        "PYPI_INDEX_URL": "https://pypi.org/pypi",
        "PYPI_INDEX_URLS": "https://mirrors.aliyun.com/pypi/simple/,https://pypi.tuna.tsinghua.edu.cn/simple/",
        "PYPI_CACHE_TTL": "3600",
        "PYPI_LOG_LEVEL": "INFO"
      }
    }
  }
}

With Private Repository

{
  "mcpServers": {
    "pypi-query": {
      "command": "uvx",
      "args": ["--from", "mcpypi", "mcpypi"],
      "env": {
        "PYPI_INDEX_URL": "https://pypi.org/pypi",
        "PYPI_PRIVATE_PYPI_URL": "https://private.pypi.company.com",
        "PYPI_PRIVATE_PYPI_USERNAME": "your_username",
        "PYPI_PRIVATE_PYPI_PASSWORD": "your_password",
        "PYPI_CACHE_TTL": "3600"
      }
    }
  }
}

Cline

Add to your Cline MCP settings (cline_mcp_settings.json):

{
  "mcpServers": {
    "pypi-query": {
      "command": "uvx",
      "args": ["--from", "mcpypi", "mcpypi"],
      "env": {
        "PYPI_INDEX_URL": "https://pypi.org/simple/",
        "CACHE_TTL": "3600"
      }
    }
  }
}

Cursor

Add to your Cursor MCP configuration (.cursor/mcp.json):

{
  "mcpServers": {
    "pypi-query": {
      "command": "uvx",
      "args": ["--from", "mcpypi", "mcpypi"],
      "env": {
        "PYPI_INDEX_URL": "https://pypi.org/simple/",
        "CACHE_TTL": "3600"
      }
    }
  }
}

Windsurf

Add to your Windsurf MCP configuration (~/.codeium/windsurf/mcp_config.json):

{
  "mcpServers": {
    "pypi-query": {
      "command": "uvx",
      "args": ["--from", "mcpypi", "mcpypi"],
      "env": {
        "PYPI_INDEX_URL": "https://pypi.org/simple/",
        "CACHE_TTL": "3600"
      }
    }
  }
}

Claude Code

If you're using Claude Code, you can connect to this MCP server using the claude mcp command:

# Connect to the PyPI Query MCP server (global - available in all Claude Code instances)
claude mcp add mcpypi -- uvx mcpypi

# Connect for local development or single Claude Code instance only
claude mcp add -s local mcpypi -- uvx mcpypi

# Or with custom environment variables
claude mcp add mcpypi -- uvx mcpypi \
  --env PYPI_INDEX_URL=https://pypi.org/pypi \
  --env PYPI_CACHE_TTL=3600 \
  --env PYPI_LOG_LEVEL=INFO

# List connected MCP servers
claude mcp list

# Remove the server (global scope)
claude mcp remove mcpypi

# Remove the server (local scope)
claude mcp remove -s local mcpypi

Once connected, you can use all the MCP tools directly in Claude Code sessions by asking questions like:

• "What are the dependencies of Django?"
• "Check if numpy is compatible with Python 3.11"
• "Show me the top downloaded packages this month"
• "Analyze the security vulnerabilities in my requirements.txt file"

Environment Variables

Basic Configuration

• PYPI_INDEX_URL: Primary PyPI index URL (default: https://pypi.org/pypi)
• PYPI_CACHE_TTL: Cache time-to-live in seconds (default: 3600)
• PYPI_LOG_LEVEL: Logging level (default: INFO)
• PYPI_REQUEST_TIMEOUT: HTTP request timeout in seconds (default: 30.0)

Multiple Mirror Sources Support

• PYPI_INDEX_URLS: Additional PyPI index URLs (comma-separated, optional)
• PYPI_EXTRA_INDEX_URLS: Extra PyPI index URLs for fallback (comma-separated, optional)

Private Repository Support

• PYPI_PRIVATE_PYPI_URL: Private PyPI repository URL (optional)
• PYPI_PRIVATE_PYPI_USERNAME: Private PyPI username (optional)
• PYPI_PRIVATE_PYPI_PASSWORD: Private PyPI password (optional)

Advanced Dependency Analysis

• PYPI_DEPENDENCY_MAX_DEPTH: Maximum depth for recursive dependency analysis (default: 5)
• PYPI_DEPENDENCY_MAX_CONCURRENT: Maximum concurrent dependency queries (default: 10)
• PYPI_ENABLE_SECURITY_ANALYSIS: Enable security vulnerability analysis (default: false)

Example Configuration

# Use multiple mirror sources for better availability
export PYPI_INDEX_URL="https://pypi.org/pypi"
export PYPI_INDEX_URLS="https://mirrors.aliyun.com/pypi/simple/,https://pypi.tuna.tsinghua.edu.cn/simple/"
export PYPI_EXTRA_INDEX_URLS="https://test.pypi.org/simple/"

# Private repository configuration
export PYPI_PRIVATE_PYPI_URL="https://private.pypi.company.com"
export PYPI_PRIVATE_PYPI_USERNAME="your_username"
export PYPI_PRIVATE_PYPI_PASSWORD="your_password"

Available MCP Tools

The server provides 37 comprehensive MCP tools across 8 categories:

Core Package Information (11 tools)

1. get_package_info - Get comprehensive package information
2. get_package_versions - List all available versions for a package
3. get_package_dependencies - Analyze package dependencies
4. check_package_python_compatibility - Check Python version compatibility
5. get_package_compatible_python_versions - Get all compatible Python versions
6. resolve_dependencies - Recursively resolve all package dependencies with detailed analysis
7. download_package - Download package and all dependencies to local directory
8. get_download_statistics - Get comprehensive download statistics for any package
9. get_download_trends - Analyze download trends and time series data (last 180 days)
10. get_top_downloaded_packages - Get the most popular packages by download count
11. search_pypi_packages - Advanced PyPI package search with intelligent fallbacks

PyPI Publishing & Account Management (6 tools)

12. upload_package_to_pypi - Upload packages to PyPI with comprehensive validation
13. check_pypi_credentials - Validate PyPI authentication credentials
14. get_pypi_upload_history - Get detailed upload history and statistics
15. delete_pypi_release - Delete specific package releases from PyPI
16. manage_pypi_maintainers - Add/remove package maintainers
17. get_pypi_account_info - Get comprehensive PyPI account information

Package Metadata & Management (4 tools)

18. update_package_metadata - Update package descriptions, keywords, and metadata
19. manage_package_urls - Update project URLs and documentation links
20. set_package_visibility - Control package visibility and access
21. manage_package_keywords - Add/remove package keywords and tags

Analytics & Insights (4 tools)

22. get_pypi_package_analytics - Comprehensive package analytics and metrics
23. get_pypi_security_alerts - Security vulnerability alerts and advisories
24. get_pypi_package_rankings - Package popularity rankings and comparisons
25. analyze_pypi_competition - Competitive analysis with similar packages

Discovery & Monitoring (4 tools)

26. monitor_pypi_new_releases - Monitor new package releases and updates
27. get_pypi_trending_today - Get trending packages with growth metrics
28. search_pypi_by_maintainer - Find packages by maintainer or organization
29. get_pypi_package_recommendations - Get intelligent package recommendations

Development Workflow (4 tools)

30. validate_pypi_package_name - Validate package names and availability
31. preview_pypi_package_page - Preview package page before publishing
32. check_pypi_upload_requirements - Validate package before upload
33. get_pypi_build_logs - Retrieve build logs and debugging information

🔒 Security Analysis (2 tools)

34. scan_pypi_package_security - Comprehensive security vulnerability scanning with OSV database and GitHub advisories
35. bulk_scan_package_security - Bulk security scanning for multiple packages with consolidated reporting

📄 License & Compliance (2 tools)

36. analyze_pypi_package_license - License compatibility analysis with SPDX normalization and risk assessment
37. check_bulk_license_compliance - Bulk license compliance checking with comprehensive compatibility matrix

🏥 Package Health Assessment (2 tools)

• assess_package_health_score - Package health scoring across 7 categories (maintenance, popularity, documentation, testing, security, compatibility, metadata)
• compare_packages_health_scores - Comparative health analysis between multiple packages with GitHub metrics integration

📋 Requirements Analysis (2 tools)

• analyze_requirements_file_tool - Requirements file analysis supporting multiple formats (requirements.txt, pyproject.toml, setup.py, Pipfile, conda.yml)
• compare_multiple_requirements_files - Multi-file comparison for requirements analysis across different environments

MCP Prompt Templates (12 tools)

• analyze_package_quality - Generate comprehensive package quality analysis prompts
• compare_packages - Generate detailed package comparison prompts
• suggest_alternatives - Generate prompts for finding package alternatives
• resolve_dependency_conflicts - Generate prompts for resolving dependency conflicts
• plan_version_upgrade - Generate prompts for planning package version upgrades
• audit_security_risks - Generate prompts for security risk auditing
• plan_package_migration - Generate comprehensive package migration plan prompts
• generate_migration_checklist - Generate detailed migration checklist prompts
• analyze_environment_dependencies - Generate prompts for analyzing current environment dependencies
• check_outdated_packages - Generate prompts for checking outdated packages with update priorities
• generate_update_plan - Generate prompts for creating comprehensive package update plans
• analyze_daily_trends - Generate prompts for analyzing daily PyPI download trends

📖 Learn more about prompt templates: See PROMPT_TEMPLATES.md for detailed documentation and examples.

Usage Examples

Once configured in your MCP client (Claude Desktop, Cline, Cursor, Windsurf), you can ask questions like:

Basic Package Queries

• "What are the dependencies of Django 4.2?"
• "Is FastAPI compatible with Python 3.9?"
• "Show me all versions of requests package"
• "What Python versions does numpy support?"
• "Get detailed information about the pandas package"

Advanced Dependency Analysis

• "Please help me analyze the complete dependency tree for PySide2 with Python 3.10"
• "Resolve all dependencies for Django including development dependencies"
• "What are all the transitive dependencies of FastAPI?"

Package Download

• "Please help me download PySide2 and all its dependencies for Python 3.10 to my local machine"
• "Download the requests package with all dependencies to ./downloads folder"
• "Collect all packages needed for Django development"

Download Statistics & Popularity Analysis

• "What are the download statistics for the requests package this month?"
• "Show me the download trends for numpy over the last 180 days"
• "What are the top 10 most downloaded Python packages today?"
• "Compare the popularity of Django vs Flask vs FastAPI"
• "Which web framework has the highest download count this week?"

MCP Prompt Templates

• "Use the analyze_package_quality prompt to evaluate the requests package"
• "Generate a comparison prompt for Django vs FastAPI vs Flask for building APIs"
• "Create a migration plan prompt for moving from Flask to FastAPI"
• "Help me resolve dependency conflicts with a structured prompt"
• "Generate a security audit prompt for my production packages"

Environment Analysis

• "Analyze my current Python environment dependencies and check for outdated packages"
• "Check which packages in my environment have security updates available"
• "Generate an update plan for my production environment with conservative strategy"
• "Help me identify packages that need immediate updates vs. planned updates"

Trending Analysis

• "What are the most downloaded Python packages today?"
• "Show me trending packages in the machine learning domain this week"
• "Track recent security updates and new package releases"
• "Find rising packages in web development that I should consider"

Security Analysis

• "Scan Django for security vulnerabilities using OSV database"
• "Check my requirements.txt file for packages with known security issues"
• "Bulk scan all packages in my project for security vulnerabilities"
• "What security advisories exist for numpy version 1.21.0?"

License Analysis & Compliance

• "Analyze the license compatibility of MIT, Apache-2.0, and GPL-3.0 licenses"
• "Check if all packages in my requirements.txt are compatible with my MIT license"
• "What are the licensing risks of using this package in a commercial project?"
• "Bulk check license compliance for my entire dependency tree"

Package Health Assessment

• "Assess the overall health score of the requests package"
• "Compare the health scores of Django vs FastAPI vs Flask for a new project"
• "Which package has better maintenance: numpy or pandas?"
• "Score this package across maintenance, popularity, and security metrics"

Requirements File Analysis

• "Analyze my requirements.txt file for outdated packages and security issues"
• "Compare my development and production requirements files"
• "Parse my pyproject.toml file and suggest package updates"
• "What dependencies in my Pipfile need security updates?"

Example Conversations

User: "Check if Django 4.2 is compatible with Python 3.9"

AI Assistant: I'll check Django 4.2's compatibility with Python 3.9 for you.

[Uses get_package_info and check_package_python_compatibility tools]

User: "What are the main dependencies of FastAPI?"

AI Assistant: Let me get the dependency information for FastAPI.

[Uses get_package_dependencies tool]

User: "Show me the download statistics for the requests package and tell me which is more popular: requests or urllib3?"

AI Assistant: I'll get the download statistics for both packages and compare their popularity.

[Uses get_download_statistics tool for both packages]

Programmatic Usage

# Example: Check if Django is compatible with Python 3.9
result = await mcp_client.call_tool("check_package_python_compatibility", {
    "package_name": "django",
    "target_python_version": "3.9"
})

# Example: Get package information
info = await mcp_client.call_tool("get_package_info", {
    "package_name": "requests"
})

# Example: Get download statistics
stats = await mcp_client.call_tool("get_download_statistics", {
    "package_name": "numpy",
    "period": "month"
})

# Example: Get top downloaded packages
top_packages = await mcp_client.call_tool("get_top_downloaded_packages", {
    "period": "week",
    "limit": 10
})

Development Status

🎉 Core functionality implemented and ready for use!

Current implementation status:

• ✅ Basic project structure
• ✅ PyPI API client with caching
• ✅ MCP tools implementation (package info, versions, dependencies)
• ✅ Python version compatibility checking
• ✅ Advanced dependency analysis and recursive resolution
• ✅ Package download with dependency collection
• ✅ Download statistics and popularity analysis
• ✅ Top packages ranking and trends
• ✅ CI/CD pipeline with multi-platform testing
• ⏳ Private repository support (planned)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.