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mcp-laya

by dockndevai
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Python
Local

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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

    A3.5/5.0

    Scored across 8 tools

    Disambiguation3/5

    classify, score, and check are single-question wrappers around decide's choice/score/noul modes, so an agent choosing between decide and a specialized tool may face ambiguity for a one-off task. Their descriptions clearly separate the single-vs-multiple use cases, but the underlying semantics overlap.

    Naming Consistency4/5

    All tool names are lowercase and start with an imperative verb, with compound names following verb_noun (detect_language, explain_routing, list_models). The single-word verbs (decide, classify, score, check, triage) are a minor stylistic deviation from the compound pattern but remain predictable.

    Tool Count4/5

    Eight tools is a reasonable size for a decision-model server and stays inside the ideal 3-15 range. The count is slightly padded, though, because classify/score/check are specialized versions of decide's three question types.

    Completeness4/5

    The set covers general and specialized decisions, ready-made triage presets, language detection, routing explanation, and model listing—no obvious dead ends for inference workflows. Minor gaps include no queryable preset list or way to register custom presets, but these can be worked around.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources