ListingGood helps Amazon sellers optimize product listings for search rankings and AI shopping recommendations. Check listing compliance and AI readability, generate SEO-optimized titles and descriptions, analyze negative reviews, and draft plans of action for account suspensions and policy violations.
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Encrypted at rest, isolated from the model
Resolved from an AES-256-GCM vault at the moment of the call and attached to the request — the model never sees the secrets.
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Score how likely Amazon's AI (Rufus, COSMO) is to recommend a listing. Free, deterministic, rule-based check on pasted listing copy (title, bullets, description). Returns a compliance health score, an AI-readability score, and a combined AI Recommendation Readiness Score (compliance * 0.55 + readability * 0.45) with actionable suggestions. Use this as a fast baseline BEFORE generating or editing a listing. Do NOT use it for a full compliance report - use compliance_scan for the deep knowledge-base audit. Free, read-only, no API key required, no credits deducted. Args: text: raw listing title + bullets + description (required). marketplace: marketplace code, US/DE/ES/FR/IT/JP/AE/SA/UK (default US). lang: zh or en (default en). email: optional lead email for a confirmation message and lead capture.
Score whether a product listing is Agent-Ready for AI shopping agents (ACP/UCP era). Platform-agnostic: works for Amazon, Shopify, Walmart, TikTok Shop or any storefront that AI shopping assistants may read. Use it when a user asks whether their product will be found, recommended, or auto-purchased by an AI agent. Fully local, deterministic rule engine — no API key, no credits, no network call. Returns four dimensions: structured attributes, entity clarity, trust & compliance, and agent actionability, plus ranked fixes. Args: text: raw product copy — title plus bullets/description (required). platform: amazon | shopify | walmart | tiktok | generic | auto (default auto-detected). lang: en or zh for the report language (default en).
Quick pre-publish compliance gate before generating a listing. Fast, free scan for obvious red-line words and category risks. Returns a shallow pass/fail-style result, not a full audit. Use this as a cheap pre-check right before generation. Do NOT use it for a complete risk report - use compliance_scan for the deep knowledge-base audit. Read-only; requires an API key; no credits deducted. Args: text: listing copy (required). lang: zh or en (default en). category: optional category hint, e.g. electronics or apparel.
Deep knowledge-base compliance audit (async; 2 credits). Produces a thorough, written risk report covering prohibited words, IP, category mismatches, GPSR and more, backed by a private 15-year compliance knowledge base. Use this when you need a complete, actionable compliance report. Do NOT use it for a quick pre-publish check - use compliance_check for that. Read-only; deducts 2 credits; runs asynchronously, poll for the result. Args: text: listing title/bullets/description (required). marketplace: marketplace code (default US). category: optional category hint. lang: zh or en (default en). images: optional list of up to 5 data:image base64 strings, each < 4MB.
Draft a submission-ready Plan of Action (POA) from an Amazon violation notice (async; 4 credits). Converts a suspension or removal email into a structured POA appeal. Use this when a listing or account is suppressed. Not free - deducts 4 credits and runs asynchronously, poll for the result. Read-only: it drafts text and does not submit anything to Amazon. Args: text: violation notice or removal email text (required). marketplace: marketplace code (default US). lang: zh or en (default en). violation_type: optional, e.g. ip_complaint / authenticity / policy.
Analyze a negative Amazon review for root cause and a suggested response (async; 2 credits). Extracts the underlying issue from a critical review and drafts a brand-appropriate response angle. Use this after a negative review appears, to decide how to reply. Do NOT use it to generate a listing or an appeal - use generate_listing or generate_poa for those. Read-only; deducts 2 credits; runs asynchronously, poll for the result. Args: text: the negative review text (required). marketplace: marketplace code (default US). lang: zh or en (default en).
Expand a one-sentence product description into structured listing fields (free; API key; no credits). Turns casual, spoken product copy into structured fields (title, bullets, features) that feed the listing generator. Use this as a low-friction starting point when you only have a rough sentence. Do NOT use it to produce a final optimized listing - use generate_listing for that. Read-only; free; no credits deducted. Args: sentence: one-sentence product description, 4-1000 characters (required). lang: zh or en (default en).
Generate a high-conversion Amazon listing - title + bullets + description (async; 1 credit per marketplace). Produces A9-optimized copy that respects per-marketplace character limits. Use this to create a full listing from product facts. Not free - deducts 1 credit per selected marketplace and runs asynchronously, poll for the result. Read-only: it drafts text and does not publish. Args: cn_name: product Chinese name (required). sku: product SKU (required). marketplaces: optional list of marketplace codes; defaults to all 9. price: optional product price. lang: zh or en (default en).
One endpoint, the same key, whichever client you use.
~/Library/Application Support/Claude/claude_desktop_config.json (Mac) · %APPDATA%\Claude\claude_desktop_config.json (Windows)
Replace API_KEY with your own key.
Already have an "mcpServers" section in your config? Just add the server entry inside it.
Discovery, routing, credentials, tool scoping and execution logs all happen at the gateway→connections stay ACTIVE with no work from you
ListingGood MCP runs through a gateway that holds the credentials, scopes the access and records every call.
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