GitHub.Issue.Searcher.MCP
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The GitHub Issue Searcher MCP is a powerful Model Context Protocol (MCP) Server that integrates FAISS and OpenAI embeddings to enable semantic search capabilities for GitHub repository issues.
The GitHub Issue Searcher MCP is designed to enhance the way developers and project managers interact with GitHub issues by providing a semantic search capability. By leveraging the power of FAISS (Facebook AI Similarity Search) and OpenAI embeddings, this server allows users to perform fast and accurate searches through GitHub repository issues. This tool is particularly useful for building Retrieval-Augmented Generation (RAG) systems and creating comprehensive knowledge bases focused on issue tracking. The server is compatible with Claude and other MCP clients, ensuring seamless integration into existing workflows. With features like automatic syncing of GitHub repositories, persistent storage of indexes and metadata, and fast similarity search, the GitHub Issue Searcher MCP is an invaluable tool for anyone looking to streamline their issue management process.
Features
- Semantic Search: Generate embeddings using OpenAI and search with FAISS.
- Document Storage: Store text with rich metadata for organized retrieval.
- GitHub Integration: Automatically sync and search GitHub repository issues.
- Fast Similarity Search: Powered by Facebook's FAISS library.
- MCP Compatible: Works seamlessly with Claude and other MCP clients.
Tools
search_embeddings
Search for similar content using natural language.
get_index_status
Check what data is currently indexed.