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Alternatives to docsearch-mcp

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    Related Servers

    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and MCP hosts to search and query a local hybrid vector/BM25 index of scattered notes, docs, PDFs, Office files, web pages, org files, and chat exports. It returns section-level citations so agents can ground answers in the user's own files.
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI clients to search and read a folder of Markdown/text documents via a read-only MCP server with hybrid BM25 and local embedding search, treating the calling model as untrusted.
      11 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to search local text and Markdown collections using keyword BM25, semantic vector search, and reranked hybrid retrieval, with full-document retrieval and collection status over MCP.
      1
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables fast local hybrid search over a folder of markdown files via MCP, combining BM25 and vector similarity with explicit relevance verdicts and no LLM or network calls at query time.
      1
      -
    • A
      license
      A
      quality
      A
      maintenance
      Semantic code search for any MCP client: indexes local folders of code and docs and answers plain-language or code queries with matching passages, file paths, line ranges and scores. Embedding runs on the local CPU with the Motherlode code-search encoder, so no file content leaves the machine; the encoder downloads once from Hugging Face. Install: npx -y blackwindow-weave-mcp.
      6
      4
      30 npm
      Business Source 1.1
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
      4
      -

    TDQS

    B3.3/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have clearly distinct purposes: one searches content by relevance, the other enumerates indexed sources. There is no realistic way to confuse a BM25 search with listing sources.

    Naming Consistency5/5

    Both names follow the same verb_noun snake_case pattern (search_docs, list_sources). The convention is predictable and readable.

    Tool Count3/5

    Two tools is thin for a search server; useful capabilities like fetching a full document or filtering search by source are absent. Still, the count is not absurd for a narrowly scoped read-only index.

    Completeness3/5

    Core retrieval and source enumeration are covered, but there is no way to retrieve a whole document, filter searches by source, or manage the index. Agents hitting a chunk boundary or needing document-level context will dead-end.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues