A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.
A Model Context Protocol server providing vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage.
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 server that enables semantic search capabilities by providing tools to manage Qdrant vector database collections, process and embed documents using various embedding services, and perform semantic searches across vector embeddings.
A Model Context Protocol server for ingesting, chunking and semantically searching documentation files, with support for markdown, Python, OpenAPI, HTML files and URLs.
