GitHub Agentic Chat MCP Server
by akhidasTech
This is an MCP server implementation for GitHub agentic chat using Go. It provides tools for interacting with GitHub through natural language and includes vector search capabilities.
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What is GitHub Agentic Chat MCP Server?
The GitHub Agentic Chat MCP Server is a Go-based server that enables natural language interaction with GitHub. It utilizes the Model Context Protocol (MCP) to connect with clients like Claude Desktop, allowing users to search repositories, create issues, and perform semantic search on stored documents.
How to use GitHub Agentic Chat MCP Server?
To use the server, you need to clone the repository, set up environment variables (GitHub token, database URL, OpenAI API key), configure PostgreSQL with the pgvector extension, build the server, and configure your MCP-compatible client (e.g., Claude Desktop) to point to the server's executable. Then, you can use the available tools through your client to interact with GitHub and the vector store.
Key features of GitHub Agentic Chat MCP Server
Search GitHub repositories
Create issues
Vector search functionality (add documents, semantic search)
Extensible structure for adding more features
Use cases of GitHub Agentic Chat MCP Server
Automating GitHub tasks through natural language
Quickly finding relevant repositories based on semantic queries
Storing and searching documentation related to GitHub projects
Creating issues based on user requests
Integrating GitHub functionality into chat applications
FAQ from GitHub Agentic Chat MCP Server
What is MCP?
What is MCP?
MCP stands for Model Context Protocol. It's a protocol that allows language models to interact with external tools and services.
What is pgvector?
What is pgvector?
pgvector is a PostgreSQL extension that enables efficient storage and retrieval of vector embeddings, which are used for semantic search.
Do I need an OpenAI API key?
Do I need an OpenAI API key?
Yes, an OpenAI API key is required for certain functionalities, likely related to generating embeddings for vector search.
Can I use this with other MCP-compatible clients besides Claude Desktop?
Can I use this with other MCP-compatible clients besides Claude Desktop?
Yes, as long as the client supports the Model Context Protocol and can be configured to communicate with the server.
How do I add more tools to the server?
How do I add more tools to the server?
The server has an extensible structure, allowing you to add more features by implementing new tools and integrating them into the MCP framework.