MCP server exposing a RAG knowledge base as read-only tools (search_knowledge_base, ask_knowledge_base, kb_stats, kb_diagnostic) for AI clients like Claude Desktop and Cursor, enabling token-efficient document retrieval and Q&A.
A Model Context Protocol (MCP) server for Retrieval-Augmented Generation (RAG) operations. It provides tools for building and querying vector-based knowledge bases from document collections, enabling semantic search and document retrieval capabilities.
MCP server for a shared Postgres-backed knowledge base with hybrid retrieval and agentic RAG, enabling coding agents to upload, search, and ask questions over documents with cited answers.
A local RAG knowledge base MCP server that exposes semantic document search as tools using zvec for vector storage and Qwen3-Embedding for text embedding.
MCP server for a self-hosted RAG system that enables AI tools to search and retrieve grounded answers from locally ingested documents via MCP tools, with local embeddings and no API key required.
