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MCP GitHub Reader

by skydeckai

A lightweight Model Context Protocol (MCP) server for bringing GitHub repositories into context for large language models. It allows you to access and analyze GitHub repositories directly through an API.

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What is MCP GitHub Reader?

The MCP GitHub Reader is a server that allows you to access and analyze GitHub repositories programmatically. It uses the Model Context Protocol (MCP) to provide context from GitHub repositories to large language models (LLMs).

How to use MCP GitHub Reader?

The server can be installed globally or locally using npm. Once installed, it can be run as a standalone server or integrated with tools like Claude. The server provides several tools via API to retrieve file contents, analyze repositories, and search for files.

Key features of MCP GitHub Reader

  • API-based access to GitHub repositories

  • Repository analysis and statistics

  • File access with filtering options

  • Smart caching to avoid API limits

  • Search capabilities within repositories

  • MCP Compatible

  • Ready-to-use prompt templates

Use cases of MCP GitHub Reader

  • Providing context from GitHub repositories to LLMs

  • Analyzing the structure and content of GitHub repositories

  • Searching for specific code or files within repositories

  • Automating code review and analysis

  • Building LLM-powered tools for software development

FAQ from MCP GitHub Reader

Does it support private repositories?

No, currently it only works with public GitHub repositories.

Is authentication required?

No, it does not support authentication at the moment.

What are the API rate limits?

It is subject to GitHub API rate limits (60 requests per hour for unauthenticated requests).

How can I filter the files being processed?

You can use the include_patterns and exclude_patterns parameters to filter files based on glob and regex patterns.

What is the Model Context Protocol (MCP)?

It is a protocol that enables LLMs to interact with external tools and data sources, allowing them to access relevant context for improved performance.