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    Pypi Query Mcp Server

    A Model Context Protocol (MCP) server for Python package intelligence, providing structured queries for PyPI packages and GitHub repositories. Features include dependency analysis, version tracking, and package metadata retrieval for LLM interactions.

    8 stars
    Python
    Updated Sep 26, 2025

    Table of Contents

    • Features
    • Installation
    • Using uvx (recommended)
    • Using pip
    • From source
    • Configuration
    • Claude Code (Recommended)
    • Claude Desktop
    • With Private Repository
    • Cline
    • Cursor
    • Windsurf
    • Environment Variables
    • Basic Configuration
    • Multiple Mirror Sources Support
    • Private Repository Support
    • Advanced Dependency Analysis
    • Example Configuration
    • Available MCP Tools
    • Core Package Information
    • Python Compatibility
    • Advanced Dependency Analysis
    • Download Statistics & Popularity
    • MCP Prompt Templates
    • Environment Analysis Templates
    • Trending Analysis Templates
    • Usage Examples
    • Basic Package Queries
    • Advanced Dependency Analysis
    • Package Download
    • Download Statistics & Popularity Analysis
    • MCP Prompt Templates
    • Environment Analysis
    • Trending Analysis
    • Example Conversations
    • Programmatic Usage
    • Development Status
    • Contributing
    • License

    Table of Contents

    • Features
    • Installation
    • Using uvx (recommended)
    • Using pip
    • From source
    • Configuration
    • Claude Code (Recommended)
    • Claude Desktop
    • With Private Repository
    • Cline
    • Cursor
    • Windsurf
    • Environment Variables
    • Basic Configuration
    • Multiple Mirror Sources Support
    • Private Repository Support
    • Advanced Dependency Analysis
    • Example Configuration
    • Available MCP Tools
    • Core Package Information
    • Python Compatibility
    • Advanced Dependency Analysis
    • Download Statistics & Popularity
    • MCP Prompt Templates
    • Environment Analysis Templates
    • Trending Analysis Templates
    • Usage Examples
    • Basic Package Queries
    • Advanced Dependency Analysis
    • Package Download
    • Download Statistics & Popularity Analysis
    • MCP Prompt Templates
    • Environment Analysis
    • Trending Analysis
    • Example Conversations
    • Programmatic Usage
    • Development Status
    • Contributing
    • License

    Documentation

    PyPI Query MCP Server

    PyPI version

    A Model Context Protocol (MCP) server for querying PyPI package information, dependencies, and compatibility checking.

    Features

    • 📦 Query PyPI package information (name, version, description, 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
    • 🎯 MCP prompt templates for guided analysis and decision-making
    • 🏢 Private PyPI repository support
    • ⚡ Fast async operations with caching
    • 🛠️ Easy integration with MCP clients

    Installation

    Using uvx (recommended)

    bash
    # Run directly with uvx
    uvx pypi-query-mcp-server
    
    # Or install and run with specific script
    uvx --from pypi-query-mcp-server pypi-query-mcp

    Using pip

    bash
    # Install from PyPI
    pip install pypi-query-mcp-server
    
    # Run the server
    python -m pypi_query_mcp.server

    From source

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

    Configuration

    Claude Code (Recommended)

    Add the PyPI Query MCP Server to Claude Code using the built-in MCP management:

    bash
    # Add with local scope (project-specific)
    claude mcp add pypi uvx pypi-query-mcp-server -s local
    
    # Add with user scope (available across all projects) 
    claude mcp add pypi uvx pypi-query-mcp-server -s user

    📖 Detailed Guide: See CLAUDE_CODE_INTEGRATION.md for comprehensive Claude Code integration documentation.

    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

    json
    {
      "mcpServers": {
        "pypi-query": {
          "command": "uvx",
          "args": ["--from", "pypi-query-mcp-server", "pypi-query-mcp"],
          "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

    json
    {
      "mcpServers": {
        "pypi-query": {
          "command": "uvx",
          "args": ["--from", "pypi-query-mcp-server", "pypi-query-mcp"],
          "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):

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

    Cursor

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

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

    Windsurf

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

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

    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

    bash
    # 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 the following MCP tools:

    Core Package Information

    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

    Python Compatibility

    4. check_package_python_compatibility - Check Python version compatibility

    5. get_package_compatible_python_versions - Get all compatible Python versions

    Advanced Dependency Analysis

    6. resolve_dependencies - Recursively resolve all package dependencies with detailed analysis

    7. download_package - Download package and all dependencies to local directory

    Download Statistics & Popularity

    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

    MCP Prompt Templates

    11. analyze_package_quality - Generate comprehensive package quality analysis prompts

    12. compare_packages - Generate detailed package comparison prompts

    13. suggest_alternatives - Generate prompts for finding package alternatives

    14. resolve_dependency_conflicts - Generate prompts for resolving dependency conflicts

    15. plan_version_upgrade - Generate prompts for planning package version upgrades

    16. audit_security_risks - Generate prompts for security risk auditing

    17. plan_package_migration - Generate comprehensive package migration plan prompts

    18. generate_migration_checklist - Generate detailed migration checklist prompts

    Environment Analysis Templates

    19. analyze_environment_dependencies - Generate prompts for analyzing current environment dependencies

    20. check_outdated_packages - Generate prompts for checking outdated packages with update priorities

    21. generate_update_plan - Generate prompts for creating comprehensive package update plans

    Trending Analysis Templates

    22. analyze_daily_trends - Generate prompts for analyzing daily PyPI download trends

    23. find_trending_packages - Generate prompts for discovering trending packages over time periods

    24. track_package_updates - Generate prompts for tracking recent package updates and releases

    📖 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"

    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

    python
    # 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.

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