GitHub MCP Server Integration

@faheema15

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faheema15

关于 GitHub MCP Server Integration

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GitHub MCP Server Integration 配置

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GitHub MCP Server Integration 工具

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概览

What is GitHub MCP Server Integration?

A Model Context Protocol (MCP) server that integrates with the GitHub API. It allows AI assistants like Claude or OpenAI GPT to fetch user profiles, list repositories, and create issues on GitHub using natural language.

How to use GitHub MCP Server Integration?

Clone the repository, install dependencies, set a GitHub personal access token in a .env file as GITHUB_TOKEN, then run uvicorn main:app --reload for local development. Alternatively, use the deployed server at https://github-mcp-server-production.up.railway.app. Register the .well-known/ai-plugin.json endpoint with an AI assistant to enable interaction.

Key features of GitHub MCP Server Integration

MCP-compliant server with OpenAPI documentation
Secure GitHub interaction using personal access token
Fetch GitHub user details
List repositories by username
Create issues on repositories

Use cases of GitHub MCP Server Integration

AI assistant retrieves authenticated user’s GitHub profile
AI assistant lists repositories for a given GitHub username
AI assistant creates an issue in a specified repository

常见问题

How do I authenticate with GitHub?

Set a GitHub Personal Access Token (PAT) with `repo` permissions as the environment variable `GITHUB_TOKEN` in your `.env` file or in Railway’s environment settings.

What endpoints does the server expose?

Three endpoints: `GET /github/user` (authenticated user info), `GET /github/repos/{username}` (list repos), and `POST /github/repos/{owner}/{repo}/issues` (create an issue).

How can I deploy the server?

Deploy on Railway: create a new project from your GitHub repo, add the `GITHUB_TOKEN` environment variable, and set the start command to `uvicorn main:app --host 0.0.0.0 --port 8000`.

What are the local development prerequisites?

Python 3.9+, a GitHub PAT with `repo` permissions, and cloned repo. Install dependencies with `pip install -r requirements.txt`, then run `uvicorn main:app --reload`.

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