Frequently Asked Questions about Pacman MCP Server

Q: What is the Pacman MCP Server? A: The Pacman MCP Server is a Model Context Protocol (MCP) server that allows LLMs and AI Agents to search and retrieve information from package repositories like PyPI, npm, crates.io, Docker Hub, and Terraform Registry.

Q: What package indices are supported by the Pacman MCP Server? A: The Pacman MCP Server supports PyPI (Python), npm (JavaScript), crates.io (Rust), Docker Hub (Docker images), and Terraform Registry (Terraform modules).

Q: How do I install the Pacman MCP Server? A: You can install it using uv (recommended), pip, or Docker. Instructions for each method are provided in the documentation.

Q: How do I configure the Pacman MCP Server? A: You need to add the server configuration to your AI Agent’s settings, specifying the command and arguments. Examples are provided for Claude.app and VS Code.

Q: What are the available tools provided by the Pacman MCP Server? A: The server provides tools to search packages, get package information, search Docker images, get Docker image information, and get the latest version of a Terraform module.

Q: Can I customize the user-agent of the Pacman MCP Server? A: Yes, you can customize the user-agent by adding the --user-agent argument to the configuration.

Q: How do I run tests for the Pacman MCP Server? A: You can run tests using uv run pytest with various options to specify the test categories or specific tests.

Q: How do I contribute to the Pacman MCP Server? A: Contributions are welcome! You can submit pull requests with new ideas, bug fixes, or enhancements.

Q: What is the license of the Pacman MCP Server? A: The Pacman MCP Server is licensed under the MIT License.

Q: What is MCP? A: MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs.

Q: How does the Pacman MCP Server integrate with UBOS? A: The Pacman MCP Server integrates seamlessly with the UBOS platform, providing AI Agents with access to a vast library of software packages, empowering them to automate tasks and solve complex problems.