Exposes RAG-related tools (query_knowledge_hub, list_collections, get_document_summary) via the Model Context Protocol, enabling AI assistants to perform hybrid search, document ingestion, and evaluation on knowledge bases.
A Model Context Protocol server that exposes a hybrid RAG pipeline (dense+sparse retrieval with reranking) for querying an enterprise knowledge base, enabling autonomous agents to search and retrieve relevant information.
A pluggable RAG framework that exposes hybrid search, ingestion, and evaluation tools via the Model Context Protocol, enabling AI assistants like Copilot and Claude to query knowledge bases directly.
Enables querying private knowledge bases through a modular RAG pipeline with features like hybrid retrieval, reranking, and observability, exposed via the Model Context Protocol.
Enables AI agents to retrieve relevant sections from indexed files (documents, code, etc.) via hybrid semantic/BM25 search, with citations, through the Model Context Protocol.
Hybrid semantic search (dense vector + BM25) over local knowledge bases and codebases, exposed as MCP tools for AI agents to search and list knowledge bases.
