What is jar285 github mcp analyzer
GitHub Repository Analyzer MCP Server
A Model Context Protocol (MCP) server that enables Large Language Models to analyze GitHub repositories in real-time. This server provides tools for retrieving repository information, analyzing issues, accessing documentation, and visualizing activity.
Features
- Repository Information Tool: Retrieve basic metadata about GitHub repositories
- Issue Analysis Tool: List and categorize repository issues
- README Access Resource: Access repository documentation
- Commit History Tool: Analyze recent code changes
- Activity Analysis Tool: Calculate repository activity metrics
- Visualization Tool: Create visual charts of repository activity
Prerequisites
- Python 3.10 or higher
- GitHub account and Personal Access Token
Installation
- Clone this repository:
git clone <repository-url>
cd github-repo-analyzer
- Create and activate a virtual environment:
python -m venv venv
source venv`/bin/activate` # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Create a
.env
file with your GitHub API token:
cp .env.example .env
Edit the .env
file and replace your_github_token_here
with your actual GitHub Personal Access Token.
Usage
Running the Server
To start the server in development mode with the MCP Inspector:
mcp dev src/server.py
This will open a web interface in your browser where you can test the server's tools.
Registering with Claude Desktop
To register the server with Claude Desktop:
mcp install src/server.py
After registering, restart Claude Desktop. You can then interact with the GitHub Repository Analyzer by asking Claude questions about GitHub repositories.
Example Prompts for Claude
- "Can you analyze the GitHub repository 'modelcontextprotocol/python-sdk' and tell me about its purpose and activity level?"
- "What are the top 5 open issues in the 'openai/openai-python' repository?"
- "How active has the 'anthropics/anthropic-sdk-python' repository been in the last 30 days?"
- "Please read the README of the 'microsoft/TypeScript' repository and explain its main features."
- "Generate a chart showing the commit activity for 'facebook/react' over the last 60 days."
Development
Project Structure
github-repo-analyzer/
├── src/
│ ├── github_tools.py # GitHub API client implementation
│ └── server.py # MCP server implementation
├── requirements.txt # Dependencies
├── .env.example # Example environment variables
├── .gitignore # Git ignore file
└── README.md # Project documentation
Adding New Tools
To add a new tool to the server, follow these steps:
- Add the necessary functionality to the
GitHubAPIClient
class ingithub_tools.py
- Register the tool with the MCP server in
server.py
using the@server.tool
decorator - Test the tool using the MCP Inspector
Testing
To test the server, use the MCP Inspector as described in the Usage section. You can also write unit tests for the GitHub API client functionality.
Security Considerations
- Never commit your GitHub API token to version control
- Use the minimum required scopes for your GitHub token
- Be mindful of GitHub API rate limits
License
MIT License
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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