GitHub Issue Searcher MCP Server

@calumjs

Basic information

About GitHub Issue Searcher MCP Server

🔍 A Model Context Protocol (MCP) server that provides semantic search capabilities for GitHub repository issues using FAISS and OpenAI embeddings. Perfect for developers who want to quickly find relevant issues, bug reports, and discussions across GitHub repositories using natur

#github#issue-searcher#mcp #semantic-search

GitHub Issue Searcher MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "GitHub.Issue.Searcher.MCP": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

GitHub Issue Searcher MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is GitHub Issue Searcher MCP?

GitHub Issue Searcher MCP is a Model Context Protocol (MCP) server that combines FAISS (Facebook AI Similarity Search) with OpenAI embeddings to provide semantic search for GitHub repository issues. It is designed for building Retrieval-Augmented Generation (RAG) systems and searchable knowledge bases from GitHub issue tracking data.

How to use GitHub Issue Searcher MCP?

Install Python 3.8+, set up a virtual environment, install dependencies, set OPENAI_API_KEY (and optionally GITHUB_PERSONAL_ACCESS_TOKEN) in a .env file. Run python sync_github.py owner/repo --clear to sync a repository. Configure the MCP client (e.g., Claude Desktop) to point to main.py. Then use MCP tools like search_embeddings to query natural language and get_index_status to inspect indexed data.

Key features of GitHub Issue Searcher MCP

Semantic search using OpenAI embeddings and FAISS
Document storage with rich metadata
Automatic syncing of GitHub repository issues
Fast similarity search powered by FAISS
Works seamlessly with Claude and other MCP clients
Persistent automatic saving of indexes and metadata

Use cases of GitHub Issue Searcher MCP

Semantically search through GitHub repository issues
Build searchable knowledge bases from GitHub issues
Enhance AI responses with relevant issue context (RAG)
Find similar bug reports, feature requests, or discussions
Troubleshoot developer support by searching issue history

Frequently asked questions

What are the dependencies and runtime requirements?

Python 3.8 or higher, an OpenAI API key, and optionally a GitHub Personal Access Token. Install required packages via `pip install -r requirements.txt`.

Where does the indexed data live?

The FAISS index is stored as `faiss_index.bin` and metadata as `metadata.json`, both inside a `data/` directory created automatically.

Can I add more repositories without losing existing data?

Yes, run `python sync_github.py owner/repo` without the `--clear` flag to append new repository data to the existing index.

How do I replace all data with a different repository?

Use the `--clear` flag when syncing: `python sync_github.py new-owner/new-repo --clear`.

What transport or protocol does the server use?

It implements the Model Context Protocol (MCP) and is configured to work with MCP clients like Claude Desktop via command-line invocation.

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