Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
Enables agent tools like Claude Code and GitHub Copilot to perform knowledge retrieval using hybrid search (BM25 + dense) with reranking, via MCP protocol.
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context
Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.