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ApparelHub-AI

apparelhub-mcp

Official

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      Enables AI assistants to run a print-on-demand store by creating products on Printify, pricing from production cost, publishing to Shopify and its sales channels, and generating ad creative from mockups.
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    • A
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      Enables AI agents to operate a Store Builder site end-to-end — designing pages, filling them with data, reviewing screenshots, and publishing — without human intervention.
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    TDQS

    A3.5/5.0

    Scored across 123 tools

    Disambiguation4/5

    Most tools have clearly distinct resource/action targets, and descriptions actively steer between close neighbors (ship_product vs the split primitives, find_garments vs browse_catalog, cascade_price_change vs update_product). Still, with 123 tools there are overlapping clusters—design generation/processing, analytics, and workspace copy/move/check—where misselection remains possible despite the detailed guidance.

    Naming Consistency4/5

    The dominant convention is snake_case verb_noun (list_my_products, create_product, sync_to_channel, approve_order_hold), used consistently across most resources. A few names deviate into noun phrases or less predictable forms (analytics_summary, channel_performance, listing_changes, api_request), but they remain readable rather than chaotic.

    Tool Count1/5

    123 tools is an extreme mismatch for a single MCP server, far beyond the 50+ threshold for a 1. Even given ApparelHub's broad domain, this volume imposes severe discoverability and context-selection costs, and many adjacent tools likely could be consolidated or grouped.

    Completeness5/5

    The surface covers the full lifecycle: design upload/generation/QC/archive, product creation, variants, store/fulfillment/channel sync, ordering, holds, issues, collections, workspaces, members, settings, analytics, and an API escape hatch. No obvious CRUD or lifecycle dead ends are apparent.

    Maintenance

    ActivityNo data
    ResponsivenessUnresponsive