%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Github MCP Server 1zs
A GitHub repository Model Context Protocol (MCP) server based on the Python SDK, providing repository content access functions for AI assistants.
rating : 2 points
downloads : 34
What is the GitHub MCP Server?
This is an intelligent server based on the Model Context Protocol (MCP), specifically designed for GitHub repositories. It allows AI assistants to securely access the contents of your code repositories, including files, historical modification records, issue discussions, and collaboration requests, helping developers manage projects more efficiently.How to use the GitHub MCP Server?
You can connect an AI assistant to a GitHub repository through simple API calls. First, you need to configure server access permissions, and then the AI assistant can understand your code context and answer related questions.Use cases
It is particularly suitable for scenarios that require AI-assisted code review, automatic documentation generation, intelligent Q&A systems, code history analysis, etc. Development teams can quickly gain project insights through AI.Main features
Repository content accessAI can read files and directory structures in the repository and understand the code content
Commit history trackingView code modification history to understand the change process and reasons
Issue managementAccess and search issue discussions to help solve development problems
Pull request integrationGet PR information and change content to assist with code review
Security controlProtect your code security through authentication and permission management
Advantages and limitations
Advantages
Seamlessly connect AI with GitHub repositories to enhance development efficiency
Standardized protocol ensures compatibility with various AI assistants
Built - in cache mechanism reduces the number of GitHub API calls
Flexible permission control system protects sensitive code
Limitations
Requires GitHub API access permissions
Large repositories may require query performance optimization
Currently only supports the Python language environment
How to use
Environment preparation
Ensure that Python 3.8 or a higher version is installed and prepare a GitHub access token
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%230080ff;%20}%20%3c/style%3e%3c/defs%3e%3cpath%20class='st0'%20d='M16.2,11.1c.4.5.4,1.2,0,1.8l-4.7,7.1h-3.8l5.3-8L7.6,4h3.8l4.7,7.1Z'/%3e%3c/svg%3e)
Get the server code
Clone the repository to the local development environment
Set up a virtual environment
Create and activate a Python virtual environment to avoid dependency conflicts
Install dependencies
Install all necessary Python packages
Configure environment variables
Copy the example configuration file and modify it according to your settings
Start the server
Run the development server to start using
Usage examples
Code review assistanceThe AI assistant can analyze changes in pull requests and point out potential problems or improvement suggestions
Automatic issue responseBased on historical issues and code context, the AI can automatically generate issue response suggestions
Code search and navigationQuickly locate the implementation code location of a specific function
Frequently Asked Questions
What kind of GitHub permissions are required?
How to restrict AI access to specific files or directories?
What is the server performance? Can it handle large repositories?
Does it support private repositories?
How to deploy to a production environment?
Related resources
Official MCP protocol documentation
Understand the detailed specifications of the Model Context Protocol
Python SDK repository
Python implementation of the MCP protocol
Deployment guide
How to deploy the server to platforms such as Heroku
API reference
Complete API endpoint documentation
Featured MCP Services
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
867
4.3 points
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
178
4.5 points
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.8K
5 points
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
130
4.3 points
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
595
5 points
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.7K
4.5 points
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
784
4.8 points
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.3K
4.7 points