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  • F
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    Provides a documentation search MCP tool (search_docs) that enables AI agents to retrieve relevant chunks from BDC documentation using semantic embeddings and keyword search, with filtering by document type and date.
    1
  • A
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    quality
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    Enables searching and retrieving documents from a local folder to ground LLM answers in your files.
    2
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Live, ranked search across any number of llms.txt documentation sites - Strands, Kiro, the AWS guides, and whatever you add at runtime.
    7
    37
    MIT
  • A
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    quality
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    A Model Context Protocol (MCP) server that gives AI assistants direct access to live AVEVA PI System documentation, eliminating hallucination on PI-specific topics.
    3
    MIT
  • A
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    maintenance
    MCP server that gives AI assistants direct access to live AVEVA PI System documentation, eliminating hallucination on PI-specific topics by fetching real answers from the official docs.
    3
    MIT
  • A
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    Provides AI assistants with intelligent access to project documentation and API references through smart search, contextual rules, and Docset integration. Enables AI to understand project-specific conventions, patterns, and official framework documentation without token limits.
    11
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    6
    MIT
  • A
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    quality
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    maintenance
    An MCP server for the Delovye Linii logistics API, enabling cargo delivery cost calculation, order creation, tracking, and directory lookups for cities and terminals.
    6
    42
    MIT
  • A
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    Enables searching and retrieving content from Lark (Feishu) documents via MCP tools, supporting Doc and Wiki types with OAuth authentication.
    2
    4
    MIT
  • A
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    quality
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    MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.
    MIT
  • A
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    quality
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    maintenance
    A local-first semantic search server for documents, supporting PDFs, Office files, and text/markdown, enabling natural language search via the Model Context Protocol (MCP).
    1
    MIT
  • F
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    quality
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    maintenance
    Enables semantic search and AI-powered Q&A over ingested GitHub documentation repositories via MCP tools.
  • -
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    quality
    B
    maintenance
    Enables MCP-based access to Adhoc documentation, providing search, content retrieval, and feedback issue creation with audience gating and leak protection.
  • F
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    Not graded
    quality
    B
    maintenance
    Local documentation search server for AI models using hybrid retrieval (phrase, keyword, vector). Provides MCP tools to search and fetch documentation from bundled or custom doc sets without any external API keys.
  • F
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    quality
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    maintenance
    MCP server that provides live Odoo documentation (v15.0–v19.0+) in clean Markdown, enabling AI assistants to search, fetch, and export official Odoo user and developer docs.
  • F
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    Not graded
    quality
    B
    maintenance
    Enables hybrid document search (BM25 + vector) with Reciprocal Rank Fusion over the Atlas corpus, returning ranked chunks from documents.