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github.com/loonghaoVersion Control19Updated 5w ago

About repo-template

PyPI Query MCP Server provides structured queries for PyPI packages, including metadata, dependencies and Python version compatibility. It is aimed at developers who want an LLM to retrieve Python package information.

Key features

  1. 01Query package versions, descriptions and metadata
  2. 02Check Python version compatibility
  3. 03Recursively resolve dependencies
  4. 04Download packages with their dependencies
  5. 05Retrieve download statistics and top rankings

Use cases

  1. 01Confirming whether a package supports a target Python version
  2. 02Analyzing transitive dependencies of a project
  3. 03Comparing download popularity of Python web frameworks

MCP support

This project is an MCP server that exposes package query, dependency analysis and download statistics tools to MCP clients, along with prompt templates.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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)
# 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
# Install from PyPI
pip install pypi-query-mcp-server

# Run the server
python -m pypi_query_mcp.server
From source
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:

# 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

{
  "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
{
  "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):

{
  "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):

{
  "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):

{
  "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
# 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
  1. check_package_python_compatibility - Check Python version compatibility
  2. get_package_compatible_python_versions - Get all compatible Python versions
Advanced Dependency Analysis
  1. resolve_dependencies - Recursively resolve all package dependencies with detailed analysis
  2. download_package - Download package and all dependencies to local directory
Download Statistics & Popularity
  1. get_download_statistics - Get comprehensive download statistics for any package
  2. get_download_trends - Analyze download trends and time series data (last 180 days)
  3. get_top_downloaded_packages - Get the most popular packages by download count
MCP Prompt Templates
  1. analyze_package_quality - Generate comprehensive package quality analysis prompts
  2. compare_packages - Generate detailed package comparison prompts
  3. suggest_alternatives - Generate prompts for finding package alternatives
  4. resolve_dependency_conflicts - Generate prompts for resolving dependency conflicts
  5. plan_version_upgrade - Generate prompts for planning package version upgrades
  6. audit_security_risks - Generate prompts for security risk auditing
  7. plan_package_migration - Generate comprehensive package migration plan prompts
  8. generate_migration_checklist - Generate detailed migration checklist prompts
Environment Analysis Templates
  1. analyze_environment_dependencies - Generate prompts for analyzing current environment dependencies
  2. check_outdated_packages - Generate prompts for checking outdated packages with update priorities
  3. generate_update_plan - Generate prompts for creating comprehensive package update plans
Trending Analysis Templates
  1. analyze_daily_trends - Generate prompts for analyzing daily PyPI download trends
  2. find_trending_packages - Generate prompts for discovering trending packages over time periods
  3. 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
# 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.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.