GitHub Repository Inspector

Integrates with GitHub repositories to enable repository searching, issue management, and pull request handling through authenticated API endpoints that format data for easy access within conversations.

Installation Instructions

README: https://github.com/Jehan26/MCP-Inspector-v0.6.0

MCP-Inspector-v0.6.0

GitHub MCP Server

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with GitHub repositories, issues, and pull requests.

Features

• Repository Search: Find GitHub repositories based on search queries
• Issue Management: Get, create, and comment on issues
• Pull Request Handling: View and manage pull requests
• Repository Analysis: Get statistics and insights about repositories

Installation

Prerequisites

• Python 3.8+
• GitHub API token

Steps

1. Clone this repository:

   git clone https://github.com/yourusername/github-mcp-server.git
   cd github-mcp-server
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up your GitHub token as an environment variable:

   export GITHUB_TOKEN=your_github_token_here
   

4. Run the server:

   python server.py
   

The server will start running on http://localhost:5000.

Usage

Endpoints

The MCP server provides the following endpoints:

• GET /mcp/discover: Returns available operations and their parameters
• POST /mcp/execute: Executes operations based on provided parameters

Example Requests

Discovery

curl -X GET http://localhost:5000/mcp/discover

Execute Repository Search

curl -X POST http://localhost:5000/mcp/execute \
  -H "Content-Type: application/json" \
  -d '{
    "endpoint": "search_repositories",
    "parameters": {
      "query": "machine learning"
    }
  }'

Get Repository Issues

curl -X POST http://localhost:5000/mcp/execute \
  -H "Content-Type: application/json" \
  -d '{
    "endpoint": "get_repo_issues",
    "parameters": {
      "owner": "openai",
      "repo": "whisper"
    }
  }'

Architecture

The server follows the Model Context Protocol specification to allow AI assistants to:

1. Discover available operations
2. Execute operations with appropriate parameters
3. Process and return results in a structured format

Extending the Server

You can extend this server by:

1. Adding new endpoints in the discover() function
2. Implementing corresponding handler functions
3. Updating the routing in the execute() function

Security Considerations

• The server uses an API token for authentication with GitHub
• Implement rate limiting to prevent abuse
• Add input validation for all parameters
• Consider implementing OAuth for more secure token management

Demo

See the demo video for a walkthrough of the server's capabilities.

License

MIT License

Contact

For questions or support, please open an issue on this repository.