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pubmed-search-mcp

by u9401066
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Python
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    TDQS

    A3.7/5.0

    Scored across 41 tools

    Disambiguation4/5

    Most tools target a distinct resource+action, and the descriptions actively disambiguate the riskiest clusters (find_related_articles vs find_citing_articles vs get_article_references, and fulltext vs details vs figures vs text-mined terms). Residual overlap exists in the institutional-access cluster (test_institutional_access vs diagnose_institutional_access vs get_institutional_link) and between build_citation_tree and the single-hop citation tools, but an agent can still pick correctly from the docs.

    Naming Consistency4/5

    Nearly all 41 tools use snake_case verb_noun (get_fulltext, search_gene, build_citation_tree, list_pipelines, unschedule_pipeline), which makes the surface predictable and groupable. The only real deviation is unified_search (adjective_noun, no verb), plus the mildly inconsistent use of fetch_/get_ for article details.

    Tool Count3/5

    The domain is genuinely broad (literature search, citation networks, gene/compound/ClinVar lookups, images, fulltext, export, notes, pipelines, institutional access, sessions), so a large surface is defensible. Still, 41 tools is heavy, and several clusters are inflated — 7 pipeline-lifecycle tools and 5 institutional-access tools — pushing well past the comfortable 3-15 range.

    Completeness4/5

    Coverage is unusually thorough: end-to-end search with query/PICO planning, citation graph traversal, metrics, fulltext and figures, export, and even pipeline scheduling plus persistent research chronicles with diffs. Gaps are minor — notes can only be saved (no read/list/delete counterpart), and there is no direct author/journal browse beyond unified_search.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources