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tapsifood-mcp

by sepehr071
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Python
Remote

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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

    A4.2/5.0

    Scored across 11 tools

    Disambiguation4/5

    Descriptions carefully delineate overlapping tools (tf_search_vendors vs tf_restaurants vs tf_discounted_vendors; tf_search_dishes vs tf_deals vs tf_menu) by explaining open-now vs closed results and index-lag caveats. However the vendor-finding trio and dish-finding trio still share real surface area, so an agent must read carefully to pick.

    Naming Consistency4/5

    All tools use a consistent tf_ prefix and snake_case, with clear verb_noun forms (tf_find_location, tf_list_cities, tf_search_dishes). A few are noun-only (tf_restaurants, tf_deals, tf_menu, tf_reviews, tf_vendor_info), a minor deviation but still highly readable and predictable.

    Tool Count5/5

    Eleven tools is well within the sweet spot and each covers a distinct capability (geocoding, city list, dish/vendor search, restaurant browse, deals, discount campaign, menu, vendor info, reviews). Nothing feels redundant or padding.

    Completeness4/5

    The server covers the discovery-to-decision lifecycle thoroughly: location resolution, city coverage, search, browse, menu, true-cost info, and reviews. Gaps are coupons (explicitly not exposed) and any ordering/cart actions, which appear out of scope for this info-oriented surface.

    Maintenance

    ActivityNo data
    ResponsivenessNo issues

    Resources