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

  • A
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    quality
    C
    maintenance
    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
    1
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.
    17
  • F
    license
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    quality
    D
    maintenance
    Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.
  • A
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    quality
    C
    maintenance
    MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    A secure database query service built on FastMCP framework that allows users to query MySQL databases using natural language, with comprehensive permission management and security controls.
    15
  • A
    license
    C
    quality
    D
    maintenance
    Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data including querying, creating, updating, and deleting entities through SAP BTP integration.
    19
    49
    6
    MIT
  • A
    license
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    quality
    C
    maintenance
    A generic MCP (Model Context Protocol) server for any Hugo blog, deployed on Cloudflare Workers. It reads your blog's llms.txt and llms-full.txt files and exposes them as structured tools that AI assistants can query to understand your content.
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    Enables querying a hybrid-retrieval RAG pipeline (dense + BM25) over ingested PDF documents, returning answers generated by Gemini.
  • A
    license
    Not graded
    quality
    D
    maintenance
    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
    4
    Apache 2.0
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables LLMs to perform conceptual search over local PDF/EPUB documents using a RAG pipeline with corpus-driven concept extraction and WordNet enrichment.
    3
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables semantic search over local Markdown documentation using hybrid retrieval combining embeddings, keyword search, and graph traversal with automatic file watching and zero-configuration setup.
    2
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    An MCP server that provides tools to load and fetch documentation from any llms.txt source, giving users full control over context retrieval for LLMs in IDE agents and applications.
    1,030
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    Local MCP server that provides a search_documents tool to query a RAG pipeline built with Ollama embeddings and ChromaDB, enabling Claude Desktop to retrieve relevant document chunks.
  • F
    license
    Not graded
    quality
    B
    maintenance
    A CLI tool and MCP server that turns markdown documentation into a searchable, queryable knowledge base.
    280