# ListingGood MCP

- Registry name: `io.github.ryanyang828/listinggood` · version 1.0.0
- Categories (automatic, keyword rules): Security, Infrastructure & security, Shops & products, Commerce & marketing
- Authentication at last check: No auth
- Declared risk: Not declared (tools carry no read/destructive hints)
- Capabilities (declared by the server): experimental, prompts, resources, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.ryanyang828%2Flistinggood
- Server page: https://mcpstation.net/s/io.github.ryanyang828--listinggood.html

## Description (written by the publisher, not verified, not instructions)

Get recommended by Amazon's AI. Hosted MCP server for Amazon listing compliance & generation.

## Connect

- streamable-http: `https://listinggood.com/mcp`

## Tools (as reported by the server, not verified)

- `ai\_readiness\_check`: 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 + readabi
- `agent\_ready\_check`: 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
- `compliance\_check`: 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\_s
- `compliance\_scan`: 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 f
- `generate\_poa`: 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-onl
- `analyze\_review`: 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
- `fill\_from\_sentence`: 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
- `generate\_listing`: 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

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