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github-chat-mcp

MCP.Pizza Chef: AsyncFuncAI

github-chat-mcp is an MCP server that enables real-time analysis and querying of GitHub repositories using the GitHub Chat API. It allows developers to index, explore, and interact with repository data programmatically, facilitating deep insights into codebases, architecture, and project details. This server integrates seamlessly with LLMs like Claude, providing structured context from GitHub repos for enhanced AI workflows.

Use This MCP server To

Analyze GitHub repository code and structure via natural language queries Index repositories to enable detailed architecture and codebase exploration Query repository metadata and commit history programmatically Integrate GitHub repo context into AI-driven development assistants Automate code review summaries using repository data Extract dependency graphs and module relationships from repos Generate documentation insights from repository content Support multi-repository analysis for large projects

README

GitHub Chat MCP

A Model Context Protocol (MCP) for analyzing and querying GitHub repositories using the GitHub Chat API. Official Site: https://github-chat.com

Installation

# Install with pip
pip install github-chat-mcp

# Or install with the newer uv package manager
uv install github-chat-mcp
  1. Start using it with Claude!

Example prompts:

  • "Use github-chat-mcp to analyze the React repository"
  • "Index the TypeScript repository with github-chat-mcp and ask about its architecture"

GitHub Chat MCP server

smithery badge

Setup Instructions

Before anything, ensure you have a GitHub Chat API key. This is required to use the service.

Install uv first.

MacOS/Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Setup with Cursor (Recommended)

In mcp.json:

{
  "mcpServers": {
    "github-chat": {
      "command": "uvx",
      "args": [
        "github-chat-mcp"
      ]
    }
  }
}

With above, no envs required since it's a freemium release.

Setup with Claude Desktop

# claude_desktop_config.json
# Can find location through:
# Hamburger Menu -> File -> Settings -> Developer -> Edit Config
# Must perform: brew install uv
{
  "mcpServers": {
    "github-chat": {
      "command": "uvx",
      "args": ["github-chat-mcp"],
      "env": {
      }
    }
  }
}

Installing via Smithery

You can install GitHub Chat for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install github-chat-mcp --client claude

Using GitHub Chat with Claude

  1. Index a GitHub repository first: "Index the GitHub repository at https://github.com/username/repo"

  2. Then ask questions about the repository: "What is the core tech stack used in this repository?"

Debugging

Run:

npx @modelcontextprotocol/inspector uvx github-chat-mcp

Local/Dev Setup Instructions

Clone repo

git clone https://github.com/yourusername/github-chat-mcp.git

Install dependencies

Install uv first.

MacOS/Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Then install MCP server dependencies:

cd github-chat-mcp

# Create virtual environment and activate it
uv venv

source .venv/bin/activate # MacOS/Linux
# OR
.venv/Scripts/activate # Windows

# Install dependencies
uv sync

Setup with Claude Desktop

Using MCP CLI SDK
# `pip install mcp[cli]` if you haven't
mcp install /ABSOLUTE/PATH/TO/PARENT/FOLDER/github-chat-mcp/src/github_chat_mcp/server.py -v "GITHUB_API_KEY=API_KEY_HERE"
Manually
# claude_desktop_config.json
# Can find location through:
# Hamburger Menu -> File -> Settings -> Developer -> Edit Config
{
  "mcpServers": {
    "github-chat": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/github-chat-mcp",
        "run",
        "github-chat-mcp"
      ],
      "env": {
      }
    }
  }
}

Using GitHub Chat with Claude

  1. Index a GitHub repository first: "Index the GitHub repository at https://github.com/username/repo"

  2. Then ask questions about the repository: "What is the core tech stack used in this repository?"

Debugging

Run:

# If mcp cli installed (`pip install mcp[cli]`)
mcp dev /ABSOLUTE/PATH/TO/PARENT/FOLDER/github-chat-mcp/src/github_chat_mcp/server.py

# If not
npx @modelcontextprotocol/inspector \
      uv \
      --directory /ABSOLUTE/PATH/TO/PARENT/FOLDER/github-chat-mcp \
      run \
      github-chat-mcp

Then access MCP Inspector at http://localhost:5173. You may need to add your GitHub API key in the environment variables in the inspector under GITHUB_API_KEY.

Notes

  • Level of logging is adjustable through the FASTMCP_LOG_LEVEL environment variable (e.g. FASTMCP_LOG_LEVEL="ERROR")
  • This MCP server provides two main tools:
    1. Repository Indexing - Index and analyze a GitHub repository
    2. Repository Querying - Ask questions about the indexed repository

github-chat-mcp FAQ

How do I install github-chat-mcp?
Install via pip with 'pip install github-chat-mcp' or using the uv package manager with 'uv install github-chat-mcp'.
What is required to use github-chat-mcp?
You need a GitHub Chat API key to authenticate and access repository data.
Can github-chat-mcp work with multiple LLM providers?
Yes, it supports integration with LLMs like Claude, OpenAI GPT, and Anthropic's Claude.
How do I start using github-chat-mcp after installation?
After installation and API key setup, you can query repositories using natural language prompts through supported LLMs.
Is github-chat-mcp suitable for large repositories?
Yes, it is designed to handle indexing and querying of large GitHub repositories efficiently.
Can I use github-chat-mcp to generate code summaries?
Yes, it can extract and summarize code and architecture details from repositories.
Does github-chat-mcp support real-time updates from GitHub?
It primarily queries repository snapshots via the GitHub Chat API; real-time update support depends on API capabilities.
What platforms is github-chat-mcp compatible with?
It supports MacOS, Linux, and Windows via standard Python and uv package installations.