Amazon Ads MCP
개요
제작자가 쓴 설명(영어 원문)
Amazon Ads API MCP server for Amazon Advertising API
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- 사용자 의견i아직 리뷰가 없어요리뷰는 다음 단계에서 계정 기능과 함께 열려요
- 우리의 기본 점검i1개 중 1개 통과공개된 정보로 점검했으며, 코드는 아직 스캔하지 않았어요
- 사용 정도i아주 새로움★ –
할 수 있는 일
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
- 연결 방식: 클라우드에서 실행
- 전송 방식: Streamable HTTP
- 카테고리: 마케팅 및 소셜 미디어
설치
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
설치하기 전에
- 기본 점검: 1개 중 1개 통과
- 제작자의 서버에서 실행돼요. 내가 요청한 내용은 제작자의 서버를 거쳐요.
- 직접 입력할 값:
Authorization
필요한 것
- 클라우드에서 실행설치할 것 없음. 인터넷으로 연결돼요
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
터미널에서 이 명령어를 실행하세요
claude mcp add --transport http amazon-ads 'https://{HOSTNAME}/mcp' --header 'Authorization: Bearer {AUTH_TOKEN}'실행하기 전에 빈 값을 채워 주세요.
주소에 나만 아는 {…} 부분(예: 내 계정)이 있어서, 복사한 뒤 직접 채워 주세요.
또는 설정을 직접 복사하기
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"amazon-ads": {
"url": "https://{HOSTNAME}/mcp",
"headers": {
"Authorization": "Bearer {AUTH_TOKEN}"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
주소에 나만 아는 {…} 부분(예: 내 계정)이 있어서, 복사한 뒤 직접 채워 주세요.
또는 설정을 직접 복사하기
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"amazon-ads": {
"type": "http",
"url": "https://{HOSTNAME}/mcp",
"headers": {
"Authorization": "Bearer {AUTH_TOKEN}"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
직접 입력할 값
AuthorizationHTTP headerBearer credential required by the selected Amazon Ads MCP deployment.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
할 수 있는 일
주소에 내 값이 필요해서 대신 도구 목록을 읽을 수 없어요.
기본 점검i
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
- ✓ 통과
제작자와 저장소 일치
레지스트리 이름이 GitHub 계정 KuudoAI 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
- … 아직 점검 안 함
계속 관리되고 있음
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
- … 아직 점검 안 함
라이선스 있음
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
- – 해당 없음
엔드포인트 응답
주소에 내 계정 값이 필요해서 대신 점검할 수 없어요
- – 해당 없음
OAuth로 로그인
주소에 내 계정 값이 필요해서 대신 점검할 수 없어요
- … 아직 점검 안 함
도구 설명에 숨겨진 지시 없음
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
마케팅 및 소셜 미디어 카테고리의 다른 서버와 비교i
- 이 카테고리의 다른 서버 3597개 중 0%보다 스타가 많아요
- 이 카테고리의 다른 서버 3597개 중 94%보다 최근에 레지스트리에 공개됐어요
- 기본 점검 결과가 이 카테고리의 다른 서버 3597개 중 100%와 같거나 더 좋아요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
자주 묻는 질문
Amazon Ads MCP, 안전한가요?
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
어떤 키나 코드가 필요한가요?
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
아직 관리되고 있나요?
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.33)은 어제 레지스트리에 올라왔어요.
어떤 앱에서 쓸 수 있나요?
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
대신 쓸 수 있는 건 뭐가 있나요?
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
대안
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Google Analytics MCP
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
BibiGPT YouTube Video Summarizer
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
제작자의 README
README 열기
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Kuudo Amazon Ads MCP Server
The open-source Amazon Ads MCP server from [Kuudo](https://www.kuudo.com/), also published as the Amazon Ads API MCP SDK
*Made with ❤️ + ☕ by Kuudo, an Openbridge company*
MCP registry id (for clients and catalogs that display a stable package name): io.github.KuudoAI/amazon_ads_mcp
Kuudo's Amazon Ads MCP server gives Claude, ChatGPT, Cursor and any MCP client 711 Amazon Ads API operations across 53 services: Sponsored Products, Sponsored Brands, Sponsored Display, Sponsored TV, Amazon DSP and Amazon Marketing Cloud, with read and write tools. It is MIT-licensed. Run it yourself, or have Kuudo run it in your own AWS, Google Cloud, Azure or Cloudflare account.
Kuudo · Amazon Ads MCP · Tool reference · Compare Amazon Ads MCP servers
Table of contents
- Questions this server answers
- Where this fits in Kuudo
- What are MCP tools?
- What is Amazon Ads API MCP SDK?
- Quick start
- Installation
- Configuration (auth, packages, profiles, regions)
- Downloading reports and exports
- Example MCP client (Claude Desktop)
- Context limits
- Code mode
- Tool audit
- Background tasks
- Frequently asked
- Troubleshooting
- Documentation map
Questions this server answers
Which MCP server connects Claude or ChatGPT to Amazon Ads, including DSP and Amazon Marketing Cloud?
Kuudo's Amazon Ads MCP covers all three in one server: Sponsored Products, Brands, Display and TV, Amazon DSP, and Amazon Marketing Cloud, 711 Amazon Ads API operations across 53 services, with read and write tools. It works from Claude, ChatGPT, Cursor and any other MCP client. See how it compares with the other Amazon Ads MCP servers: kuudo.com/compare/amazon-ads-mcp-servers.
Can I self-host an Amazon Ads MCP server in my own AWS or GCP account?
Yes. This server is MIT-licensed and runs from Docker or Python on infrastructure you control. Kuudo also provisions it, with the Selling Partner and Vendor Central servers, into your own AWS, Google Cloud, Azure or Cloudflare account, where Amazon requests go from your cloud directly to Amazon: self-host Kuudo in your own cloud.
Does it cover Seller Central and Vendor Central too?
This repository is the Amazon Ads server. Kuudo runs companion MCP servers for Seller Central (listings, inventory, orders, pricing, fulfillment and reports) and Vendor Central (purchase orders, shipments, invoices and Retail Analytics), and one AI client can use all three at once.
Can an agency run it across many client accounts?
Yes, through Kuudo. Each client authorizes its Amazon Ads account once through a time-limited invitation, with no login shared, and one connection then reaches every account and advertising profile the agency is authorized for: how account authorization works.
How is it different from Amazon's own Ads MCP Server?
Amazon's Ads MCP Server is hosted by Amazon and in open beta for Amazon Ads partners with active API credentials. This server is open source, runs where you choose, and works with your own Amazon Ads app or a partner token. The side-by-side, with every source dated: Amazon Ads MCP Server vs Kuudo.
Where this fits in Kuudo
This repository is the tool layer of a broader Amazon agent platform. Kuudo gives Amazon agents tools, knowledge, workflows, and a place to work. This repository is the tools.
| Layer | What it provides | Where |
|---|---|---|
| MCP servers | The tools an agent calls: Amazon Ads here, plus Selling Partner and Vendor Central | this repo, and the MCP tool reference |
| Skills | The higher-level workflows: reusable, versioned, multi-step Amazon procedures that compose these tools and wait for a human before anything goes live | Amazon Agent Skills |
| Agent Atlas | The knowledge: indexed Amazon operating knowledge across Ads, Seller Central, and Vendor Central, answered with citations | Amazon Agent Atlas |
| Agent Flow | The place to work: your Amazon data landed in your own cloud, so an agent answers with real figures instead of guessing | Amazon Agent Flow |
Read this repository as one layer of that platform rather than as the whole of it. The operations below are what an agent can call; Skills are what it runs.
What Are MCP Tools?
Think of MCP (Model Context Protocol) as a translator between an AI model and outside systems (like Amazon Ads). Each MCP tool is like a remote control button that tells the AI how to interact with Amazon Ads. Without MCP tools, the AI would have no idea how to “talk” to Amazon Ads.
With MCP tools:
- The AI knows the exact endpoints to call.
- The AI can request campaign reports, budgets, or targeting data safely.
- Everything is structured, so the AI doesn’t break things by making random guesses.
👉 In short: MCP tools = a safe, well-labeled toolkit that lets AI work with the Amazon Ads API.
🚀 What is Amazon Ads API MCP SDK?
The Amazon Ads API MCP SDK is an open-source implementation that provides a robust foundation for creating AI-powered advertising tools, chatbots, and automated services.
✨ Key Features
- 🔌 MCP Integration: Full Model Context Protocol compliance for AI application integration
- 🌍 Multi-Region Support: NA, EU, and FE region endpoints with automatic routing
- 📊 Comprehensive API Coverage: Campaigns, profiles, reporting, DSP, AMC workflows, and more
- 📝 Type Safety: Full Pydantic model support with comprehensive type hints
- 🧪 Production Ready: Includes testing, validation, and error handling
🎯 Use Cases
Claude Desktop Integration
- Campaign Management: Ask Claude to create, update, or analyze campaigns
- Performance Insights: Get AI-powered analysis of your advertising performance
- Budget Optimization: Let Claude suggest budget adjustments based on performance
- Creative Testing: Get recommendations for ad creative improvements
- Reporting: Generate custom reports and insights on demand
AI Applications
- Marketing Chatbots: Build conversational AI that can manage Amazon Ads campaigns
- Automated Reporting: AI-powered insights and performance analysis
- Smart Budget Management: Intelligent budget optimization using AI
- Creative Optimization: AI-driven ad creative testing and optimization
Enterprise Services
- Marketing Automation Platforms: Integrate Amazon Ads into existing marketing tools
- Agency Management Systems: Multi-client, multi-account advertising management
- E-commerce Integrations: Connect Amazon Ads with e-commerce platforms
- Analytics Dashboards: Real-time advertising performance monitoring
Developer Tools
- API Wrappers: Create custom SDKs for specific use cases
- Testing Frameworks: Automated testing for Amazon Ads integrations
- Development Tools: Local development and debugging utilities
Why this Ads MCP is different
Other Amazon Ads MCPs do happy path. They fall apart the moment an agent makes a reasonable mistake and Amazon's Ads API has more reasonable mistakes than almost any other large API surface. The v1 reporting catalog uses a different vocabulary than v3. The docs are scattered across migration generations. The same field can have three plausible names depending on which tutorial an agent or human was trained on.
You've felt this before
You know the symptoms even if you've never thought of them as a single problem:
- "Compacting conversation…" right when you were getting somewhere
- "Usage limit reached" mid-task, with nothing to show for the tokens
- "Context window exceeded" start over, re-explain everything
- The agent quietly forgetting the fix it figured out three turns ago
- Five tool calls, four of them retries, none of them progress
- Re-pasting the same error into the chat for the third time
That's not the model being dumb. That's the API surface burning context vague errors trigger thrashing, thrashing fills the window, the window fills and everything useful gets evicted. Anywhere from 4 to 12 round-trips for an agent: wrong field names, wrong body shape, wrong filter operator, wrong date placement, wrong advertiser-account format.
Here, the wrong moves return the right move
This server is built around a different premise: the error surface is the documentation surface. Every failure is a teaching opportunity, and the server is engineered to make the next attempt smarter than the last one, for the same agent or the next one, without retraining, prompt updates, or memory tricks.
- The server tells you what went wrong, and *why* you got it wrong
- Every failure converts to a corrective action — the model just reads the hint and moves on
- A five-tool-call debugging arc collapses into a two-call corrected one
- The same mistake a week later doesn't re-burn context, because the validator, alias table, and deprecated-shape table are still right there
- No out-of-context tribal knowledge to forget
Every failure is cheaper than the last. Every agent learns from the same authoritative source. Every retry has direction. That compounding is what a smart agent solution looks like in practice.
Everything is an edge case, you can help
We won't catch every edge case. Amazon's API surface is enormous, the migration history is messy, and real-world failures get more creative than anything anyone can anticipate. What we're committing to is the strategy that errors should teach, that documentation should live in the surfaces agents actually touch, that every wrong move should make the next move easier.
If you hit a failure where the envelope didn't help; vague hint, wrong suggestion, no hint at all, that's exactly the feedback we want. Open an issue, paste the envelope, tell us what you expected. The strategy is only as good as the cases it covers.
Quick start
Prerequisites: Docker (recommended), Python 3.10+ if you run from source, and Amazon Ads API access (your own developer app or a partner such as Openbridge).
git clone https://github.com/KuudoAI/amazon-ads-mcp.git && cd amazon-ads-mcpcp .env.example .envand add credentials (see Configuration).- `docker compos
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요