A minimal RAG service that exposes a vector index for document retrieval via REST and MCP, allowing querying for relevant document chunks and returning a suggested LLM prompt.
A private, self-hosted RAG service over MCP that enables document ingestion, hybrid retrieval (BM25 + dense vectors fused with RRF), and notebook management through 14 tools, keeping documents on your own hardware.
MCP server that enables querying an HR FAQ document via RAG, returning accurate answers and related chunks, and supports index rebuilding and response evaluation.
MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.
An enterprise-ready MCP server that exposes a RAG tool for retrieving relevant context and metadata from a Qdrant vector database using natural language queries.