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.
A simple Model Context Protocol server that enables searching and retrieving relevant documentation snippets from Langchain, Llama Index, and OpenAI official documentation.
A Model Context Protocol server that provides document analysis capabilities to LLM applications, including extraction, chunking, summarization, and semantic search for PDF, DOCX, and plaintext documents.
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).
Self-hosted MCP server that indexes documentation from various sources and makes it searchable by AI assistants via the Model Context Protocol and REST API.
