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"Agentic RAG: Understanding or Exploring Its Meaning and Applications" matching MCP servers:

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    Standalone MCP server exposing agentic-RAG tools (hybrid search, article retrieval, category listing) over a pgvector-backed knowledge base with bearer-token auth, designed for deployment on Render.
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    Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.
    8
    MIT
  • A
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    A Model Context Protocol (MCP) server with Retrieval-Augmented Generation (RAG) for answering questions about imaginary SuperNova documentation. Enables semantic search over documentation using HuggingFace embeddings.
    1
    MIT
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    MCP server for RAG-based search over 1C Enterprise configuration documentation, enabling natural language queries to find objects like справочники, документы, and отчеты.
    MIT
  • A
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    Enables querying Confluence or Kubernetes documentation through hybrid search and an agentic RAG pipeline, returning structured answers with citations.
    Apache 2.0
  • F
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    MCP server exposing a RAG knowledge base as read-only tools (search_knowledge_base, ask_knowledge_base, kb_stats, kb_diagnostic) for AI clients like Claude Desktop and Cursor, enabling token-efficient document retrieval and Q&A.
  • F
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    Provides read-only MCP tools for hybrid semantic and keyword search over locally indexed PDF documentation, with citations and context retrieval for LLM agents.
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    An MCP server that enables users to query Kedro framework documentation using retrieval-augmented generation. It builds a local knowledge base from documentation files to help users navigate and apply Kedro's data science pipeline framework.
  • F
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    Retrieval-Augmented Generation system serving LangGraph documentation through the Model Context Protocol, enabling semantic search and context-aware responses.
    16
  • A
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    An MCP server that guides AI assistants to navigate documentation using their built-in tools (grep, file reading) instead of traditional RAG.
    3
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    3
    MIT
  • A
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    A local, read-only MCP server that lets coding agents search the complete AAS skill catalog, compose and validate agent-chosen skill stacks, and generate reproducible, reviewable plans without uploading project code.
    2,548
    MIT
  • A
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    An MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
    12
    MIT
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    Provides access to Godot engine documentation through a Retrieval-Augmented Generation (RAG) system using ChromaDB. It enables users to query processed Godot documentation and technical chunks for development assistance within MCP-compatible environments.
    28
    MIT