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.
A local-first semantic search server for documents, supporting PDFs, Office files, and text/markdown, enabling natural language search via the Model Context Protocol (MCP).
A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.
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.
A local document processing server that can index various document formats (PDF, DOCX, TXT, HTML) and answer questions based on their content using the Model Context Protocol.
An MCP server for document parsing, ingestion, query (including multimodal), and lightweight knowledge graph inspection, enabling RAG workflows via the Model Context Protocol.