@marketbasketanalysis/mcp
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- AlicenseNot gradedqualityCmaintenanceEnables AI shopping agents to search products, check stock, apply promotions, manage cart sessions, and create cryptographically signed checkout sessions on e-commerce storefronts, while giving merchants analytics into agent intent and catalog demand gaps.MIT

dentro MCPofficial
AlicenseAqualityDmaintenanceProvides structured commerce data for AI agents, enabling real-time product searches and brand discovery across 22,000+ DTC brands without scraping or hallucination.519 npmMIT- FlicenseNot gradedqualityDmaintenanceEnables AI agents to browse product catalogs, search products with filters, and initiate checkouts, generating order summaries and checkout URLs.-
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- FlicenseNot gradedqualityAmaintenanceEnables AI shopping agents to search products, get offers, and generate signed cart handoff links for self-hosted WooCommerce stores. Also provides a global readiness-scan tool to score any store's agent-readiness.-
- FlicenseNot gradedqualityCmaintenanceEnables AI agents to provide e-commerce customer service with product search, RAG-based FAQ answers, human handoff, and automated security auditing with a review workflow.-
TDQS
Scored across 19 tools
Most tools are clearly differentiated by resource and action (single-product vs cart vs subscription, list vs explain vs act), and several descriptions explicitly call out differences from related tools. However, the cluster of explanation tools (get_rationale, explain_opportunity, explain_drift) and the several scoring/analysis tools (score_cross_sell, analyze_basket, score_return_risk) could still cause minor selection confusion from names alone.
All tool names follow snake_case verb_noun conventions and are mostly predictable (get_*, explain_*, score_*). There are minor inconsistencies: related recommendation tools use different verbs (get_recommendations, find_substitutes, propose_subscription_bundle, get_bundle_for_cart), and predict_reorder vs forecast_bundle split an otherwise uniform forecasting concept.
With 19 tools, the server sits in the 16-25 range, which feels heavy and exceeds the ideal well-scoped 3-15 band. The count is defensible given the broad domain coverage, but agents will need to navigate a large surface to find the right tool.
The tool surface covers a comprehensive market-basket workflow: recommending, substituting, scoring, explaining, mining, alerting, forecasting, and acting on opportunities. Minor gaps exist—such as no direct tool for managing custom rules beyond triage and no bulk scoring—but the core domain is well covered with no critical dead ends.