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AI commerce for Shopify: product search, comparison, recommendations, and checkout via MCP.

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Status
Healthy
Uptime
90.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
ChatGPT
–
Claude
–

TDQS

A3.9/5.0

Scored across 11 tools

Disambiguation2/5

Substantial overlaps exist: `recommend` and `skincare_recommend` are explicitly identical (one deprecated), `create_checkout` and `skincare_cart` both produce buyable checkout URLs, and the `shop` router conceptually subsumes search_products, get_product, compare_products, and recommend. Descriptions add routing guidance, but an agent still faces real redundancy and must pick between near-duplicate paths.

Naming Consistency3/5

Names are uniformly snake_case, which is good, but the verb/prefix conventions are inconsistent: bare verbs (`shop`, `recommend`) mix with verb_noun (`get_product`, `search_products`, `compare_products`), and a `skincare_` domain prefix is applied to only some tools (`skincare_cart`, `skincare_recommend`, `skincare_report_issue`) while related tools lack it.

Tool Count4/5

11 tools is a reasonable scope for a shopping/research assistant, though one tool (`skincare_recommend`) is deprecated and redundant, effectively leaving 10, and the router-plus-granular design adds a layer that is arguably unnecessary.

Completeness4/5

The surface covers the core shopping lifecycle well: discovery (search_products), lookup (get_product), decision (compare_products, recommend), purchase (create_checkout, skincare_cart), plus research notes and a feedback channel. Only minor gaps (e.g. order management, broader research retrieval) keep it from being fully complete.

Available Tools

11 tools
compare_productsA
Read-only
Inspect

Compare two or more products side by side. Use when the user asks to compare, says 'X vs Y', or wants to decide between options. Do not use for single product lookup — use get_product instead. Returns structured comparison with shared attributes, differences, tradeoffs, and a decision hint.

Inputs: products (required).

create_checkoutAInspect

Create a checkout URL for one or more products. Pass variant IDs (items) and/or product URLs (product_urls). When a product URL is provided (e.g. https://laluer.com/products/mira), the tool resolves it to a variant ID automatically — no catalog import needed. Supports discount codes, cart notes, and selling plans. Do not use unless the user wants to buy — use search_products or skincare_recommend first. Returns a direct Shopify checkout link the user can click to buy.

Inputs: note, items, decision_id, product_urls, +1 more.

get_productA
Read-only
Inspect

Get full details for a specific product by SKU or title. Use when the user asks about a specific product by name (e.g. 'tell me about MIRA', 'show me the serum'). Do not use for browsing or recommendations — use search_products or skincare_recommend. Returns a widget card with the product details, image, price, and checkout button.

Inputs: sku, title.

get_research_noteA
Read-only
Inspect

Get the summary and URL of a specific SearchShopAI Research Note by its slug (returned by search_research_notes).

Inputs: slug (required).

recommendA
Read-only
Inspect

Get a personalized product recommendation with domain-expert scoring. Use when the user wants advice, has a concern, or asks what to buy. Returns scored products with checkout URLs.

Inputs: query (required), brand, domain, strategy.

search_productsA
Read-only
Inspect

Browse and search the product catalog. Use when the user wants to see what's available, look up specific products, browse by category, compare options, or asks 'show me' / 'what do you have.' Do not use when the user needs personalized recommendations based on skin concerns — use skincare_recommend instead. Returns all matching products with prices, images, and checkout. Unlike skincare_recommend, this does not score or filter — it shows everything that matches so the user can decide.

Inputs: query (required), category, max_price, max_results.

search_research_notesA
Read-only
Inspect

Search SearchShopAI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShopAI has written or published about a topic.

Inputs: query (required).

shopA
Read-only
Inspect

Start here for any shopping request. Pass the shopper's COMPLETE request in their own words and this tool will understand it and route to the right capability (personalized recommendation, catalog search, product lookup, or comparison), preserving every qualifier — concerns, skin type, budget, brand. Prefer this tool whenever the request is conversational or carries any nuance. The granular tools (search_products, get_product, compare_products, create_checkout) remain available as precise follow-ups.

Inputs: request (required), brand, intent, budget_max, +1 more.

skincare_cartAInspect

Create a buyable shopping cart with a real checkout URL. Two modes: (1) Pass 'products' array with specific product names. (2) Pass 'query' string to auto-recommend and cart. Do not use for browsing or recommendations — use search_products or skincare_recommend first. Returns a widget with the cart items and a working checkout link.

Inputs: query, products, strategy.

skincare_recommendA
Read-only
Inspect

(Deprecated: use 'recommend' instead. Works identically.) Get a personalized skincare recommendation with ingredient-aware scoring and routine building. Use when the user wants advice, has a skin concern, or asks what to buy. Do not use for browsing or listing products — use search_products instead. Returns scored products with checkout URLs.

Inputs: query (required), brand, strategy.

skincare_report_issueAInspect

Report when a tool result was unhelpful, incomplete, or wrong. Call this whenever you override a recommendation, skip a cart result, or notice the engine output doesn't match what the user needs. Do not use proactively — only when you observe an actual issue. This helps improve the engine.

Inputs: tool_name (required), issue_type (required), description (required), user_query, +1 more.

Tool Schema Changelog

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