semanticscholar-mcp-server
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TDQS
Scored across 22 tools
The tools are mostly distinct but there are overlapping pairs: the two recommendation tools differ only by one accepting negative examples, and the legacy tools (search_semantic_scholar, get_semantic_scholar_citations_and_references) duplicate existing search and citation/reference functionality. Descriptions help clarify, but an agent could easily pick the wrong tool.
All tools share the 'semantic_scholar' prefix, but the verb patterns are inconsistent: autocomplete, batch_get, search, bulk_search, match, recommend, list, and get are used in various orders and forms. Object naming also varies (author, author_details, author_papers, paper_details, papers), and the two legacy tools break the pattern entirely.
22 tools is on the heavy side, within the 16-25 borderline range. The server covers multiple subdomains (papers, authors, datasets, recommendations, snippets), so the count is defensible, but redundant legacy tools and overlapping recommendation helpers inflate it unnecessarily.
The tool set provides broad coverage of the Semantic Scholar API: paper and author search/retrieval, citations/references, recommendations, dataset access, and snippet search. Minor gaps exist—such as no direct tool for getting author citations or a more explicit 'get paper by DOI' separate from batch/get—but the core workflows are well-supported.