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Explainability Report MCP

by CSOAI-ORG
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Python

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.4/5.0

    Scored across 5 tools

    Disambiguation4/5

    Each tool has a distinct purpose (impact assessment, decision explanation, model card, quick scan, transparency audit). However, quick_scan and transparency_audit both assess transparency, with descriptions that are somewhat overlapping, potentially causing confusion for an agent.

    Naming Consistency3/5

    Most tools use verb_noun pattern (create_, explain_, generate_), but quick_scan uses adjective_noun and transparency_audit is noun_noun, breaking consistency. The naming is readable but not uniform.

    Tool Count5/5

    With 5 tools covering key explainability tasks (impact assessment, decision explanation, model card, scan, audit), the count is well-suited for the server's purpose, not too many or too few.

    Completeness4/5

    The tool set covers major explainability report needs (DPIA, model cards, decision explanations, transparency audits). Minor gaps exist (e.g., no tool for bias detection or combined summary), but core capabilities are present.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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