BioMCP
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TDQS
Scored across 35 tools
The tool set has clear domain separation (articles, trials, variants, etc.) but significant overlap exists between general and specialized tools. For example, 'fetch' overlaps with all the individual getters (article_getter, trial_getter, etc.), and 'search' overlaps with domain-specific searchers (article_searcher, trial_searcher, etc.). Descriptions help clarify, but agents may struggle to choose between overlapping tools.
Most tools follow a consistent verb_noun pattern (e.g., article_getter, trial_searcher, variant_getter), with verbs like 'get', 'search', and 'fetch'. However, there are deviations: 'think' and 'fetch' are single words, and 'alphagenome_predictor' uses a noun_verb pattern. Overall, naming is mostly predictable but not perfectly uniform.
With 35 tools, the count is excessive for a single server, leading to redundancy and complexity. Many tools could be consolidated (e.g., merging getters and searchers into fewer tools with parameters). This large number may overwhelm agents and increase the risk of misselection, especially given the overlapping functionalities.
The tool set provides comprehensive coverage across biomedical domains, including articles, trials, variants, genes, drugs, diseases, FDA data, and NCI resources. Each domain has both search and fetch capabilities, with detailed lifecycle support. No obvious gaps are present; the surface is well-rounded for biomedical research tasks.