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Macrocosmos MCP

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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

    A4.1/5.0

    Scored across 7 tools

    Disambiguation4/5

    Most tools target distinct resources and actions clearly: on-demand query vs. Gravity task creation are separated by scale and use case, and status/cancel tools are split by resource type. The only mild ambiguity is between query_on_demand_data and create_gravity_task, but their descriptions explicitly clarify quick vs. large-scale collection.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern (query_, create_, get_, build_, cancel_). The naming clearly indicates the action and the target resource, making the API predictable and easy to navigate.

    Tool Count5/5

    Seven tools is well-scoped for the two core workflows: on-demand queries and long-running Gravity data collection with dataset building. Each tool serves a distinct step in the lifecycle without redundancy or bloat.

    Completeness4/5

    The core lifecycle is covered: query, create task, check status, build dataset, check status, and cancel either operation. Minor gaps exist such as no listing of existing tasks/datasets and no way to retrieve a completed Gravity dataset directly without building it, but these are workable.

    Maintenance

    ActivityMaintained
    ResponsivenessWithin a week

    Resources