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 hybrid document search (BM25 and dense) over a configurable corpus via MCP tools, returning passages and sources for AI agents to cite in answers.
Enables MCP clients to query a modular RAG knowledge hub with hybrid dense/sparse retrieval, reranking, multimodal image support, and traceable observability, all through natural language tools.
Enables MCP-compatible AI agents to search, ask, and retrieve section-level cited answers from a local hybrid index over scattered notes, documents, and chat logs.
MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.