GitHub Repository Assistant MCP Server

@deploypilotorg

Repository

Basic information

About GitHub Repository Assistant MCP Server

No overview available yet

GitHub Repository Assistant MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

GitHub Repository Assistant MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is GitHub Repository Assistant?

GitHub Repository Assistant is an MCP server that connects Claude with GitHub repositories, enabling code analysis and task assistance like creating deployment workflows. It is designed for developers who want to interact with repositories through Claude.

How to use GitHub Repository Assistant?

Install Python 3.13+, Git, and set your Anthropic API key in a .env file. Install dependencies with pip install -r requirements.txt, then run streamlit run app.py. In the sidebar, enter the path to server.py and click "Connect to Server". Enter a GitHub repository URL and click "Analyze Repository" to start interacting.

Key features of GitHub Repository Assistant

Clone and analyze any GitHub repository
Interact with repositories through Claude 3.5 Sonnet
Request deployment workflows and code generation tasks
Seamless integration via Streamlit frontend
MCP server with specialized tools for repository interaction

Use cases of GitHub Repository Assistant

Understand what files exist in a repository and their purposes
Analyze specific source files like main.py for functionality
Generate a GitHub Actions workflow for deployment
Create a Dockerfile for an application

Frequently asked questions

What types of repositories are supported?

Only public GitHub repositories are currently supported.

What are the system requirements?

Python 3.13 or higher, Git installed and available in PATH, and an Anthropic API key.

How do I connect the MCP server in the Streamlit app?

In the sidebar, enter the path to the `server.py` file in the "Server Script Path" field and click "Connect to Server".

Are there any limitations on repository size?

Large repositories may take longer to clone and analyze.

Do generated workflows work immediately?

Generated deployment workflows may need manual adjustments based on specific requirements.

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