"Notes or documentation related to 'rag'" matching MCP servers:

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.

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.

An MCP server that provides AI assistants with access to Vonage API documentation, code snippets, tutorials, and troubleshooting resources.

Give your AI agents instant access to Keboola API documentation. Search endpoints, get parameter details, and generate curl examples—all through MCP tools.

Minimal local RAG stack with an MCP server that provides document search for any agent.

A Model Context Protocol server for indexing and searching local document collections with hybrid BM25+vector search, optimized for Korean and English, supporting DOCX, PDF, audio, and more.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

An MCP server that serves documentation and enables AI-powered search, Q\&A, and document analysis for developer tools and guides.

Provides AI assistants like Claude or Cursor with access to Payman AI's documentation, helping developers build integrations more efficiently.

A local-first RAG engine that ingests documents (PDF, Markdown, images, etc.) and provides hybrid search, reranking, and LLM answer synthesis via MCP for AI agent integration.

Enables AI assistants to search and retrieve information from the REMnux malware analysis toolkit documentation, allowing users to ask questions about reverse-engineering tools and get accurate, up-to-date answers from the live documentation.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

An MCP server that provides AI agents with direct access to authoritative Cakemail API specifications, enabling accurate code generation and eliminating hallucination.

Lightweight project management for teams and AI agents.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

Connect AI assistants to Manticore Search. Execute SQL queries, list tables, get schemas, and fetch documentation. Perfect for building RAG applications and search-powered AI agents.