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 citation-grounded RAG server for internal documentation that exposes retrieval tools and resources via the Model Context Protocol, enabling any MCP client to search and access organizational knowledge with structured citations.
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 server that enables document indexing and sentence window retrieval across multiple file formats like PDF, MD, and DOCX. It supports both local Hugging Face models and OpenAI embeddings for efficient context-aware querying through the Model Context Protocol.
