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MCP server for LogSeq

by ergut

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      Enables AI assistants to interact with your local Logseq knowledge base through advanced search, content creation, template management, and knowledge organization with privacy-first, local-only operations.
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    • A
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      Connects MCP-compatible AI assistants to Logseq graphs, enabling block-first operations, block references, and context graph building.
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      Enables AI assistants like Claude to directly read, write, search, and navigate your local Logseq knowledge graph, including managing journals, pages, backlinks, and page relationships without manual copy-pasting.
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    • A
      license
      Not graded
      quality
      D
      maintenance
      Connects AI assistants to Logseq knowledge graphs to read, write, and search pages, blocks, and journals via the Model Context Protocol. It features 17 tools for full graph management, including CRUD operations, batch block insertion, and full-text search.
      10 npm
      Apache 2.0

    TDQS

    A3.6/5.0

    Scored across 17 tools

    Disambiguation5/5

    Each tool targets a distinct resource and action: pages, blocks, search/query, namespaces, and properties. Overlaps like query vs find_pages_by_property are explicitly framed as simple alternatives, so an agent can choose correctly.

    Naming Consistency4/5

    Mostly consistent verb_noun snake_case (list_pages, get_block, create_page), but 'query' and 'search' are bare verbs, a minor deviation from the pattern.

    Tool Count4/5

    17 tools is slightly above the ideal 3-15 range for a cohesive set, though each covers a distinct operation. The count feels a bit heavy but not excessive for LogSeq's complexity.

    Completeness4/5

    Core CRUD for pages and blocks is covered, plus searching, querying, backlinks, and namespace navigation. Minor gaps remain (e.g., explicit block creation on a page, move/reorder operations), but agents can work around them.

    Maintenance

    ActivityMaintained
    ResponsivenessSlow