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GitHub MCP Server Configuration

GitHub MCP Server Configuration

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github.com/yosay-orgVersion Control0Updated 84w ago

About GitHub MCP Server Configuration

A documentation repository recording installation and configuration of the GitHub MCP server, for developers who need to reproduce its setup. It covers configuring a GitHub Personal Access Token and testing the server with repository search.

Key features

  1. 01Installation and configuration steps
  2. 02GitHub Personal Access Token setup
  3. 03Repository search test

Use cases

  1. 01Reproducing GitHub MCP server setup
  2. 02Configuring a token for GitHub access
  3. 03Verifying repository search

MCP support

The documentation covers installing and configuring the GitHub MCP server and records a repository-search test; it does not describe other tools or resources exposed by the server.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

GitHub MCP Server Configuration

This repository documents the setup and configuration of the GitHub MCP server on 2025-03-18.

Steps Performed

  1. Created MCP server directory and installed @modelcontextprotocol/server-github package
  2. Configured MCP server with GitHub Personal Access Token
  3. Tested server functionality with repository search
  4. Created this repository to document the configuration process

Additional Notes

Updated npm version using the following commands:

  • npm install -g npm@latest
  • npm install -g n
  • n stable

Reference: Gemini conversation about npm update

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.