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 Chroma, enabling AI models to create collections and retrieve data using vector search, full text search, and metadata filtering.
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 provides AI assistants with direct access to local document collections through full-text search, supporting multiple formats and hierarchical collections.
A Model Context Protocol server that enables semantic vector search over Obsidian notes, allowing AI assistants to intelligently search and retrieve relevant note content.
A Model Context Protocol server providing vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage.
