MCP server for document ingestion and semantic search on Qdrant. Enables ingesting local documents, generating embeddings with OpenAI, and performing vector search with metadata filters.
A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
MCP server for local semantic retrieval over a library of ebooks, using pplx-embed-context-v1 embeddings stored in Qdrant, enabling an LLM agent like Gemma 4 to search and retrieve relevant passages for answering questions.