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opentargets-mcp

by nickzren
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Python
Remote

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    TDQS

    B3.2/5.0

    Scored across 68 tools

    Disambiguation4/5

    Tools are systematically organized by entity type (disease, drug, target, variant, study) and data category, which makes most purposes clear. However, some inverse relationships like get_disease_known_drugs vs get_drug_linked_diseases and get_disease_associated_targets vs get_target_associated_diseases could initially confuse an agent, though descriptions clarify them.

    Naming Consistency5/5

    All tool names use snake_case with a consistent verb_noun pattern (get_*, search_*, map_*, graphql_*). Entity prefixes are uniform, making it predictable to infer a tool's function from its name even without reading the description.

    Tool Count2/5

    With 68 tools, the set far exceeds the 25+ threshold, making navigation and selection challenging for an agent. While the Open Targets domain is broad, this many tools likely bundles what could be a smaller set of higher-level operations or requires aggressive grouping.

    Completeness5/5

    The toolset covers the full spectrum of Open Targets data access: entity metadata, associations, evidence, literature, phenotypes, expression, safety, and advanced GraphQL. Search and batch utilities address bulk needs, and no major query need appears missing, making the surface extremely thorough.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources