ListingGood MCP

io.github.ryanyang828由 GitHub 账号 ryanyang828 发布v1.0.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行效率与工作流商业与电商

概览

AI 生成的概览

托管型 MCP 服务器，为亚马逊商品listing评分、审核并生成文案，面向 AI 推荐就绪度、合规与申诉。

可以做什么
评估 listing 的 AI 推荐就绪度与 Agent 就绪度，并给出排序后的改进建议（免费检查）。运行快速合规预检，或基于知识库的深度合规审计并输出书面报告。按站点生成 A9 优化的标题、要点和描述，或把一句话产品描述扩展为结构化字段。根据亚马逊违规通知起草行动计划（POA），并分析差评的根因与回复角度。
适用场景
适合亚马逊卖家和代运营：在发布前确认 listing 是否易被机器读取且合规，生成或本地化 listing 文案，或应对下架与差评。
运行要求
远程 Streamable HTTP 端点，无需本地安装。需要服务商开发者页面提供的 API key，以 apikey 查询参数形式放在端点 URL 中。两项免费检查（AI 就绪度、Agent 就绪度）据称无需 API key。付费工具需要积分。
安装前请注意
多个工具消耗积分：深度合规扫描 2 点、listing 生成每站点 1 点、行动计划 4 点、差评分析 2 点。API key 通过 URL 查询字符串传递，可能出现在客户端配置和日志中。listing 文案、违规通知和评论会发送到服务商的托管服务。生成的 listing 和申诉稿需人工审核后再提交。

安装

在 SourceWeft 中

  1. 打开 控制台中的 ListingGood MCP，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.ryanyang828%2Flistinggood/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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.

来源：README.md，提交 9249aba

工具

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.

输入参数langtext必填emailmarketplace

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).

输入参数langtext必填platform

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.

输入参数langtext必填category

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.

输入参数langtext必填imagescategorymarketplace

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.

输入参数langtext必填marketplaceviolation_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).

输入参数langtext必填marketplace

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).

输入参数langsentence必填

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).

输入参数sku必填langpricecn_name必填marketplaces

版本历史

1
  1. v1.0.0最新Sep 16, 2026

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度，依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价，也不表示服务器安全或当前可用：可连通性是带日期的检查结果，评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分