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"Using RAG to Provide Documentation to LLMs" matching MCP servers:

  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    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.
    3
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    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.
    MIT
  • A
    license
    Not graded
    quality
    F
    maintenance
    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.
    75
    208
    Apache 2.0
  • A
    license
    Not graded
    quality
    Not graded
    maintenance
    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.
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to create, validate, and audit llms.txt files for websites, including checking against Google Lighthouse's Agentic Browsing requirements, via Streamable HTTP with no API key needed.
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    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.
    5
  • A
    license
    A
    quality
    D
    maintenance
    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.
    5
    4
    Apache 2.0