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LLMDoc

by bigbag
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Python
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Alternatives to LLMDoc

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    Related Servers

    • doc-search by SodaShikenn

      doc-searchofficial

      SodaShikenn
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.
      MIT

    • mcp-local-rag

      xiuxiansk
      A
      license
      A
      quality
      C
      maintenance
      MCP server that enables local hybrid semantic and keyword search over private PDF, DOCX, Markdown, and text documents without sending data to embedding APIs.
      9
      3,151 npm
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    • mcp-docs

      pgupta1795
      A
      license
      Not graded
      quality
      D
      maintenance
      MCP server for documentation search that automatically indexes web documentation sites and provides semantic, full-text, or hybrid search capabilities.
      5 npm
      MIT

    • mcp-pgvector-search

      JuanPinilla198
      A
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that enables hybrid semantic and keyword retrieval over your documents, using PostgreSQL and pgvector as the backend. It fuses rankings from both methods to provide high-quality search results to the language model.
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: search_docs for global search, get_doc for full content with pagination, get_doc_excerpt for targeted extraction, list_sources for source discovery, and refresh_sources for index updates. The overlap between search_docs and get_doc_excerpt is adequately clarified by their descriptions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (search_, get_, list_, refresh_), making the API predictable and easy to navigate.

    Tool Count5/5

    With 5 tools, the server is well-scoped for a documentation search and retrieval service. Each tool is necessary and covers a distinct operation without redundancy.

    Completeness4/5

    The core workflow is covered: discover sources, search, retrieve full or excerpted content, and refresh the index. Minor gaps exist around source management (e.g., adding/removing sources) and listing all documents within a source, but these are not critical for standard usage.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources