What is GitHub Issue Searcher MCP?
GitHub Issue Searcher MCP is a Model Context Protocol (MCP) server that provides semantic search capabilities for GitHub repository issues using FAISS and OpenAI embeddings. It allows developers to quickly find relevant issues, bug reports, and discussions across GitHub repositories using natural language queries.
How to use GitHub Issue Searcher MCP?
To use the GitHub Issue Searcher MCP, clone the repository, set up a virtual environment, install dependencies, and sync a GitHub repository to populate the search index. After syncing, you can search through issues using natural language queries.
Key features of GitHub Issue Searcher MCP?
- 🔍 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.
- 💾 Persistent Storage: Automatic saving and loading of indexes and metadata.
Use cases of GitHub Issue Searcher MCP?
- Semantically searching through GitHub repository issues.
- Building searchable knowledge bases from GitHub issues.
- Enhancing AI responses with relevant GitHub issue context.
- Researching similar issues, bug reports, or feature requests.
- Supporting developers by searching through issue history for troubleshooting.
- Project management by discovering related issues and tracking patterns.
FAQ from GitHub Issue Searcher MCP?
- Can I use this tool for any GitHub repository?
Yes! You can sync and search through any public GitHub repository.
- Is there a cost associated with using GitHub Issue Searcher MCP?
No, it is open-source and free to use.
- What are the prerequisites for installation?
You need Python 3.8 or higher and an OpenAI API key. A GitHub Personal Access Token is optional for integration.