"Information on RAG Documents or Processing" matching MCP servers:

Let your AI assistant create professional Office documents — PowerPoint, Word, Excel, emails & XML — with a single prompt.

Safely downloads and extracts public tender documents from PDFs, Office files, and ZIP archives into text with structured signals, while also supporting document comparison and base64 extraction.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

RAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.

Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.

MCP bridge to a multimodal RAG service, enabling hybrid search and Q&A over documents with tools for knowledge base queries and health checks.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

MCP server that enables semantic search over PDF documents using RAG with ChromaDB and OpenAI embeddings.

MCP server for Fathom Works RAG that exposes a self-hosted knowledge base as tools for any MCP-capable LLM to query documents, manage libraries, and ingest files or URLs.

Enables AI assistants to search NHTSA recall documents and query governed dbt analytics via validated, read-only text-to-SQL, returning citable evidence and data freshness without granting database or file access.

Enables any MCP host to search and answer over your own documents with hybrid BM25+dense retrieval, cross-encoder reranking, and grounded, cited responses that refuse when no evidence is found.

Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.

Provides local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.

A server that implements Retrieval-Augmented Generation using GroundX and OpenAI, enabling semantic search and document retrieval with Modern Context Processing for enhanced context handling.

MCP server that integrates a 1200-paper RAG database with six tools to support research workflows across stages like hypothesis, experiment, statistics, and writing. It routes requests to specialized skills and real-time frontier searches to provide evidence-grounded research mentoring.

This read-only MCP Server allows you to connect to XML Documents data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for XML Documents (https://www.cdata.com/drivers/xml/download/mcp).

Enables local knowledge base management with retrieval-augmented generation (RAG), providing semantic search, document reading, listing, and Q&A via MCP tools and REST endpoints, all running locally without cloud dependencies.

Enables coding agents to retrieve relevant sections from a repository's declared documentation scope using hybrid vector and full-text search, with incremental indexing.

Enables AI assistants to search and retrieve information from your knowledge base using RAG (Retrieval-Augmented Generation) with hybrid search, document indexing, and ChromaDB vector storage.