ListingGood MCP

io.github.ryanyang828Published by GitHub account ryanyang828v1.0.0Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableProductivity & WorkflowBusiness & Commerce

Overview

AI-generated overview

Hosted MCP server that scores, audits and generates Amazon listings for AI recommendation readiness, compliance and appeals.

What you can do
Score listings for AI recommendation readiness and agent-readiness, with ranked fixes (free checks). Run a quick compliance gate or a deep knowledge-base compliance audit with a written report. Generate A9-optimized titles, bullets and descriptions per marketplace, or expand a one-sentence product description into structured fields. Draft a Plan of Action from an Amazon violation notice and analyze negative reviews for root cause and response angle.
When to use it
Useful for Amazon sellers and agencies who want to check whether a listing is machine-readable and compliance-clean before publishing, generate or localize listing copy, or respond to a suppression or negative review.
Requirements
Remote Streamable HTTP endpoint; nothing to install locally. An API key from the provider's developer page, passed as an apikey query parameter in the endpoint URL. The two free checks (AI readiness, agent readiness) are stated to need no API key. Credits are needed for paid tools.
Before you install
Several tools cost credits: deep compliance scan 2, listing generation 1 per marketplace, Plan of Action 4, review analysis 2. The API key travels in the URL query string, so it may appear in client configs and logs. Listing copy, violation notices and reviews are sent to the provider's hosted service. Generated listings and appeals are drafts to review before submission.

Installation

In SourceWeft

  1. Open ListingGood MCP in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.ryanyang828%2Flistinggood/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "listinggood": {
      "type": "http",
      "url": "https://listinggood.com/mcp"
    }
  }
}

README

ListingGood — AI Recommendation Engine (Skills + MCP)

Make AI recommend your products. ListingGood is the engine that helps Amazon's AI — Rufus, COSMO, and agentic shopping agents — find, trust, and recommend your listings. It does this through three things: compliance, AI writing, and appeal rescue.

[Website] [MCP] [Free check]

Installation

ListingGood runs as a hosted, remote Streamable HTTP MCP server — there is nothing to install locally. Just point your MCP client at the endpoint with your API key.

Endpoint:

https://listinggood.com/mcp?apikey=YOUR_API_KEY

Get your free API key at listinggood.com/developers (signup grants 10 permanent stars).

Claude Desktop / Cursor / VS Code / Windsurf / Cline

json
{  "mcpServers": {    "listinggood": {      "type": "streamable-http",      "url": "https://listinggood.com/mcp?apikey=YOUR_API_KEY"    }  }}

No Docker build, no npx command, no local Python runtime — the API key is passed as a URL query parameter (?apikey=...) exactly as shown above.

Why this exists

Amazon's discovery front-door has moved to AI. A listing that is not machine-readable and compliance-clean is far less likely to be cited inside Rufus answers, COSMO-driven recommendations, or agentic buying flows. Traditional seller tools tell you what to sell — they don't tell you whether your listing will be recommended.

ListingGood closes that gap:

  • Compliance pre-check — flags risky claims and category issues before you publish (free, no login).
  • AI readability — scores how well Amazon's AI surfaces can parse and cite your listing.
  • AI writing — generates compliant titles, bullets, and descriptions.
  • Appeal rescue — drafts a Plan of Action (POA) when a listing is suppressed.

The combined result is an AI Recommendation Readiness Score = compliance × 0.55 + AI readability × 0.45.

Available Tools

ai_readiness_check

Score how likely Amazon's AI (Rufus, COSMO) is to recommend a listing. Returns a combined AI Recommendation Readiness Score with actionable fixes. Free, no API key required.

agent_ready_check

Score whether a product listing is Agent-Ready for AI shopping agents (OpenAI ACP / Google UCP era). Platform-agnostic: Amazon, Shopify, Walmart, TikTok Shop or any storefront. Returns four dimensions — structured attributes, entity clarity, trust & compliance, agent actionability — plus ranked fixes. Free, no API key required, runs fully locally in the MCP server (no credits).

compliance_check

Fast pre-publish compliance gate: scans for red-line words and category risks before you generate or publish. Free with API key.

compliance_scan

Deep, knowledge-base-driven compliance audit across prohibited terms, IP risk, category rules, and GPSR. Returns a written report. 2 credits.

generate_listing

Generate optimized title + bullets + description for selected marketplaces. 1 credit per marketplace.

fill_from_sentence

Turn a one-sentence product description into structured listing fields. Free with API key.

generate_poa

Draft a submission-ready Plan of Action from an Amazon violation or suspension notice. 4 credits.

analyze_review

Analyze a negative review for root cause and a suggested response or POA angle. 2 credits.

What's in this repo

This repository bundles ListingGood's agent skills and MCP server config so AI agents and power users can call ListingGood programmatically:

PackageWhat it does
listinggood-expertAll-in-one Amazon listing expert: write · compliance pre-check · appeal rescue
listinggood-amazon-listing-optimizerHigh-conversion listing generation (title + bullets + description)
listinggood-amazon-compliance-auditorCompliance audit with Critical/Warning/Info grading
listinggood-deep-complianceDeep, knowledge-base-backed compliance report
listinggood-appeal-rescuePOA drafting + negative-review root-cause analysis
listinggood-amazon-title-optimizerA9/A10 title optimization
listinggood-amazon-bullet-writerBenefit-led bullet points
listinggood-amazon-eu-localizationEU marketplace (DE/ES/FR/IT) localization
MCP server8 tools (free check, Agent-Ready score, deep scan, AI generation, POA, …) + vertical MCPs (Electronics / Toys / Beauty / Home)

Quick start

  1. Get a free API key at listinggood.com/developers.
  2. Add the server to your MCP client using the config block in Installation.
  3. Restart your client. ListingGood's tools appear as available MCP tools.

Try it now (no account)

Run a free compliance + AI-readability check at listinggood.com/scan — paste your title and bullets, get a report in seconds.

Links

ListingGood AI Recommendation Engine — make AI recommend your products.

Source: README.md at commit 9249aba

Tools

8

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 + 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.

Parameterslangtextrequiredemailmarketplace

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 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).

Parameterslangtextrequiredplatform

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_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.

Parameterslangtextrequiredcategory

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 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.

Parameterslangtextrequiredimagescategorymarketplace

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-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.

Parameterslangtextrequiredmarketplaceviolation_type

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 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).

Parameterslangtextrequiredmarketplace

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 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).

Parameterslangsentencerequired

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 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).

Parametersskurequiredlangpricecn_namerequiredmarketplaces

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts