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Gondola AI

Gondola AI

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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

    A3.7/5.0

    Scored across 31 tools

    Disambiguation3/5

    Most tools target distinct resources, but hotel analytics tools blur together: search_hotels already provides side-by-side cash/points comparison that compare_rates duplicates, and predict_price/get_hotel_stats both evaluate whether a current rate is good. Detailed descriptions help, but an agent could still select the wrong value-assessment tool.

    Naming Consistency4/5

    Names overwhelmingly follow a get_/search_/create_/delete_/update_ + noun pattern, which is predictable and consistent. Minor deviations like credit_card_coverage (missing verb) and the similar get_travel_profiles/get_traveler_context pair keep it from being perfect.

    Tool Count2/5

    At 31 tools, this exceeds the 25+ threshold for 'too many' and feels heavy even for a broad travel domain. Several hotel rate and value tools could be consolidated without losing capability.

    Completeness3/5

    The server covers hotel search/comparison/booking links, flights, vehicles, loyalty, trips, and traveler context well. Notable gaps exist: no booking cancellation/update, no flight award pricing (explicitly unsupported), and no event details beyond search, which creates some dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessMixed handling

    Resources