developer-tools

Package Manager

oborchers

by oborchers

Easily search npm and other repositories with Package Manager. Get package, version, and dependency info fast. Supports

Integrates with package repositories including PyPI, npm, crates.io, Docker Hub, and Terraform Registry to search and retrieve detailed information about packages, versions, dependencies, and Docker images.

github stars

11

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Supports 5+ major package repositoriesNo API key needed

best for

  • / Developers researching package dependencies
  • / DevOps engineers managing container images
  • / Infrastructure teams working with Terraform modules

capabilities

  • / Search packages across PyPI, npm, crates.io, and Terraform Registry
  • / Get detailed package information including versions and dependencies
  • / Search Docker images on Docker Hub
  • / Retrieve Docker image metadata and tags
  • / Check latest versions of Terraform modules

what it does

Search and retrieve detailed information about packages across multiple repositories including PyPI, npm, crates.io, Docker Hub, and Terraform Registry.

about

Package Manager is a community-built MCP server published by oborchers that provides AI assistants with tools and capabilities via the Model Context Protocol. Easily search npm and other repositories with Package Manager. Get package, version, and dependency info fast. Supports It is categorized under developer tools. This server exposes 5 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Package Manager in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Package Manager is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Pacman Logo

Pacman MCP Server

A Model Context Protocol server that provides package index querying capabilities. This server enables LLMs to search and retrieve information from package repositories like PyPI, npm, crates.io, Docker Hub, and Terraform Registry.

<a href="https://glama.ai/mcp/servers/@oborchers/mcp-server-pacman"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@oborchers/mcp-server-pacman/badge" alt="mcp-server-pacman MCP server" /> </a>

Available Tools

  • search_package - Search for packages in package indices

    • index (string, required): Package index to search ("pypi", "npm", "crates", "terraform")
    • query (string, required): Package name or search query
    • limit (integer, optional): Maximum number of results to return (default: 5, max: 50)
  • package_info - Get detailed information about a specific package

    • index (string, required): Package index to query ("pypi", "npm", "crates", "terraform")
    • name (string, required): Package name
    • version (string, optional): Specific version to get info for (default: latest)
  • search_docker_image - Search for Docker images in Docker Hub

    • query (string, required): Image name or search query
    • limit (integer, optional): Maximum number of results to return (default: 5, max: 50)
  • docker_image_info - Get detailed information about a specific Docker image

    • name (string, required): Image name (e.g., user/repo or library/repo)
    • tag (string, optional): Specific image tag (default: latest)
  • terraform_module_latest_version - Get the latest version of a Terraform module

    • name (string, required): Module name (format: namespace/name/provider)

Prompts

  • search_pypi

    • Search for Python packages on PyPI
    • Arguments:
      • query (string, required): Package name or search query
  • pypi_info

    • Get information about a specific Python package
    • Arguments:
      • name (string, required): Package name
      • version (string, optional): Specific version
  • search_npm

    • Search for JavaScript packages on npm
    • Arguments:
      • query (string, required): Package name or search query
  • npm_info

    • Get information about a specific JavaScript package
    • Arguments:
      • name (string, required): Package name
      • version (string, optional): Specific version
  • search_crates

    • Search for Rust packages on crates.io
    • Arguments:
      • query (string, required): Package name or search query
  • crates_info

    • Get information about a specific Rust package
    • Arguments:
      • name (string, required): Package name
      • version (string, optional): Specific version
  • search_docker

    • Search for Docker images on Docker Hub
    • Arguments:
      • query (string, required): Image name or search query
  • docker_info

    • Get information about a specific Docker image
    • Arguments:
      • name (string, required): Image name (e.g., user/repo)
      • tag (string, optional): Specific tag
  • search_terraform

    • Search for Terraform modules in the Terraform Registry
    • Arguments:
      • query (string, required): Module name or search query
  • terraform_info

    • Get information about a specific Terraform module
    • Arguments:
      • name (string, required): Module name (format: namespace/name/provider)
  • terraform_latest_version

    • Get the latest version of a specific Terraform module
    • Arguments:
      • name (string, required): Module name (format: namespace/name/provider)

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-server-pacman.

Using PIP

Alternatively you can install mcp-server-pacman via pip:

pip install mcp-server-pacman

After installation, you can run it as a script using:

python -m mcp_server_pacman

Using Docker

You can also use the Docker image:

docker pull oborchers/mcp-server-pacman:latest
docker run -i --rm oborchers/mcp-server-pacman

Configuration

Configure for Claude.app

Add to your Claude settings:

<details> <summary>Using uvx</summary>
"mcpServers": {
  "pacman": {
    "command": "uvx",
    "args": ["mcp-server-pacman"]
  }
}
</details> <details> <summary>Using docker</summary>
"mcpServers": {
  "pacman": {
    "command": "docker",
    "args": ["run", "-i", "--rm", "oborchers/mcp-server-pacman:latest"]
  }
}
</details> <details> <summary>Using pip installation</summary>
"mcpServers": {
  "pacman": {
    "command": "python",
    "args": ["-m", "mcp-server-pacman"]
  }
}
</details>

Configure for VS Code

For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

Note that the mcp key is needed when using the mcp.json file.

<details> <summary>Using uvx</summary>
{
  "mcp": {
    "servers": {
      "pacman": {
        "command": "uvx",
        "args": ["mcp-server-pacman"]
      }
    }
  }
}
</details> <details> <summary>Using Docker</summary>
{
  "mcp": {
    "servers": {
      "pacman": {
        "command": "docker",
        "args": ["run", "-i", "--rm", "oborchers/mcp-server-pacman:latest"]
      }
    }
  }
}
</details>

Customization - User-agent

By default, the server will use the user-agent:

ModelContextProtocol/1.0 Pacman (+https://github.com/modelcontextprotocol/servers)

This can be customized by adding the argument --user-agent=YourUserAgent to the args list in the configuration.

Development

Running Tests

  • Run all tests:

    uv run pytest -xvs
    
  • Run specific test categories:

    # Run all provider tests
    uv run pytest -xvs tests/providers/
    
    # Run integration tests for a specific provider
    uv run pytest -xvs tests/integration/test_pypi_integration.py
    
    # Run specific test class
    uv run pytest -xvs tests/providers/test_npm.py::TestNPMFunctions
    
    # Run a specific test method
    uv run pytest -xvs tests/providers/test_pypi.py::TestPyPIFunctions::test_search_pypi_success
    
  • Check code style:

    uv run ruff check .
    uv run ruff format --check .
    
  • Format code:

    uv run ruff format .
    

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-server-pacman

Or if you've installed the package in a specific directory or are developing on it:

cd path/to/pacman
npx @modelcontextprotocol/inspector uv run mcp-server-pacman

Release Process

The project uses GitHub Actions for automated releases:

  1. Update the version in pyproject.toml
  2. Create a new tag with git tag vX.Y.Z (e.g., git tag v0.1.0)
  3. Push the tag with git push --tags

This will automatically:

  • Verify the version in pyproject.toml matches the tag
  • Run tests and lint checks
  • Build and publish to PyPI
  • Build and publish to Docker Hub as oborchers/mcp-server-pacman:latest and oborchers/mcp-server-pacman:X.Y.Z

Project Structure

The codebase is organized into the following structure:

src/mcp_server_pacman/
├── models/             # Data models/schemas
├── providers/          # Package registry API clients
│   ├── pypi.py         # PyPI API functions
│   ├── npm.py          # npm API functions
│   ├── crates.py       # crates.io API functions
│   ├── dockerhub.py    # Docker Hub API functions
│   └── terraform.py    # Terraform Registry API functions
├── utils/              # Utilities and helpers
│   ├── cache.py        # Caching functionality
│   ├── constants.py    # Shared constants
│   └── parsers.py      # HTML parsing utilities
├── __init__.py         # Package initialization
├── __main__.py         # Entry point
└── server.py           # MCP server implementation

Tests follow a similar structure:

tests/
├── integration/        # Integration tests (real API calls)
├── models/             # Model validation tests
├── providers/          # Provider function tests
└── utils/              # Test utilities

Contributing

We encourage contributions to help expand and improve mcp-server-pacman. Whether you want to add new package indices, enhance existing functionality, or improve documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see: https://github.com/modelcontextprotocol/servers

Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-server-pacman even more powerful and useful.

License

mcp-server-pacman is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

FAQ

What is the Package Manager MCP server?
Package Manager is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Package Manager?
This profile displays 56 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.656 reviews
  • James Reddy· Dec 28, 2024

    Package Manager is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Sakura Martin· Dec 16, 2024

    Package Manager is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Mei Flores· Dec 12, 2024

    Package Manager reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Harper Johnson· Dec 12, 2024

    Strong directory entry: Package Manager surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Dec 8, 2024

    Package Manager is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Oshnikdeep· Nov 27, 2024

    Package Manager is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Charlotte Abbas· Nov 19, 2024

    Package Manager is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Mei Zhang· Nov 7, 2024

    Package Manager is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Sakura Harris· Nov 3, 2024

    Useful MCP listing: Package Manager is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Mei Chen· Nov 3, 2024

    We wired Package Manager into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

showing 1-10 of 56

1 / 6