An MCP server that provides comprehensive multimodal Retrieval-Augmented Generation (RAG) capabilities for processing and querying document directories, supporting text, images, tables, and equations.
MCP RAG Server is a Python MCP server that indexes documents in multiple formats (Markdown, text, PowerPoint, PDF) using multilingual-e5-large embeddings and enables vector search for retrieval-augmented generation.
An MCP server for document parsing, ingestion, query (including multimodal), and lightweight knowledge graph inspection, enabling RAG workflows via the Model Context Protocol.
A Model Context Protocol server that enables any MCP-compatible application to perform advanced multi-modal document processing and retrieval using RAG-Anything.
A local RAG server using the Model Context Protocol (MCP) to allow AI assistants to query private documents with persistent memory and support for many file formats.
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.
