"Information about RAG" matching MCP servers:

A robust Model Control Protocol server that enables AI agents to access real-time cyber threat intelligence and detailed information about vulnerabilities, threat actors, malware, and other cyber-security entities.

Enables AI assistants to rewrite AI-styled English prose into more natural human writing, with tools for humanizing text and retrieving information about the underlying model.

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.

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.

Provides access to the SonoVault music metadata API, enabling search and retrieval of information about 90M+ tracks, artists, labels, and releases, including ISRC, ISWC, and cross-platform IDs.

Enables AI agents to search and retrieve detailed information about US golf courses, including course details, tees, climate, and nearby points of interest.

A Model Context Protocol server that allows AI assistants to search for and retrieve information about OpenTofu providers, modules, resources, and data sources from the OpenTofu Registry.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Provides large language models with access to news and information about renewable energy projects in Germany, allowing filtering by location, topic (solar, wind, hydrogen), and date range.

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.

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.

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.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.

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

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

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.

MCP server for searching French and European law, providing natural language access to jurisprudence, consolidated legal texts, and related legal information via tools like search_decisions and search_legal_texts.