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MCP servers tagged document-qa
11 live MCP servers tagged "document-qa", ranked by trust score. Tags come from package metadata and repository topics, so this list covers servers across every category that work with document-qa.
IncarnaMind
IncarnaMind is a free, open-source desktop app for macOS, Windows and Linux where you write with AI and ask questions about your own documents (PDF, Word, PowerPoint, Excel and mo…
IncarnaMind
The AI notebook that checks its own citations. Ask your PDFs, Word files, slides and spreadsheets; answers cite the exact page. Open-source desktop app.
OpenDocuments
Open source RAG tool for AI document search - connect GitHub, Notion, Google Drive and ask questions with cited answers. Self-hosted with Ollama/OpenAI/Claude.
Rag LLM Wiki Knowledge Base
Self-hosted RAG x LLM Wiki knowledge base framework: document parsing/chunking/vectorization, knowledge graph, hybrid retrieval (vector + graph), multi-tenant API-key isolation, s…
Local AI Lab
Hands-on course for building local, private AI from scratch - RAG, MCP, LangChain, LangGraph. Runs on your machine (Python, Node.js & C#) with Claude Code, Ollama, Gemini, or Open…
Universal File RAG
Hybrid RAG over PDFs, DOCX, spreadsheets, code repos, audio & images — explainable per-file retrieval routing (vector/hierarchical/code-graph), cited answers, and an MCP server. P…
Commission Dashboard Assistant RAG
AI-powered commission plan assistant featuring advanced RAG pipeline, Model Context Protocol (MCP) PostgreSQL server integration, multi-format document processing, and secure SELE…
Agentic Rag Chatbot MCP
Agentic RAG chatbot over PDF, DOCX, PPTX, CSV and Markdown. Multi-agent architecture, MCP-style message passing, source citations, persistent vector store.
Docwise
RAG-in-a-Box — intelligent document understanding for PDF, DOCX, and Markdown. Adaptive parsing, hybrid search (semantic + BM25), and agentic Q&A with citations. Upload, ask quest…
DocQA
A simple UI for a RAG (Retrieval Augmented Generation) backend API to query documents or URLs and get context based answers
Foveal
Multimodal working memory for agents: perceive each image once, reference it cheaply, zoom in only when needed and share what was learned across sub-agents.