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qualityC
maintenanceEnables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.
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"A server for reading documents" matching MCP servers:
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- AlicenseBqualityCmaintenanceA memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.8757MIT
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LanceDB MCP Serverofficial
FlicenseBqualityDmaintenanceA basic serverless MCP server using LanceDB to store and retrieve documents via three tools: ingest, retrieve, and get table details.325- AlicenseBqualityCmaintenanceA 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.41644MIT
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@vectros-ai/mcp-serverofficial
Alicense-qualityAmaintenanceMCP server for Vectros, a typed multi-tenant record store with hybrid search and citation-grounded RAG, enabling agents to query, search, and ask questions over their own indexed data.801Apache 2.0- Alicense-qualityDmaintenanceA Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.Apache 2.0
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- Alicense-qualityDmaintenanceAn MCP server that enables AI assistants to directly interact with Elasticsearch for searching, aggregating, and retrieving documents from indices, supporting full-text search, semantic search, and various query modes.15MIT
- Alicense-qualityDmaintenanceEnables Claude to search and retrieve documents from Azure AI Search indexes with intelligent summarization and analysis using LangGraph workflows and optional Google Gemini integration.MIT
- Alicense-qualityDmaintenanceA 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.3MIT
- Alicense-qualityDmaintenanceEnables AI assistants to query PDF documents by ingesting them into a vector database and generating answers grounded in the actual documents.111MIT
- Alicense-qualityDmaintenanceMCP RAG Server is a Python MCP server that indexes documents in multiple formats (Markdown, text, PowerPoint, PDF) using multilingual-e5-large embeddings and enables vector search for retrieval-augmented generation.MIT
MCP Server Weaviateofficial
Flicense-qualityCmaintenanceThe MCP Server for Weaviate facilitates integration with Weaviate using a customizable Python-based server, enabling interaction with Weaviate databases and OpenAI APIs via configurable URL and API keys.162