Amazon Ads MCP

Name: Amazon Ads MCP
Author: KuudoAI

제작자: KuudoAI버전 0.2.4i★ –i내 컴퓨터에서 실행

레지스트리 이름io.github.tspicer/amazon_ads_mcp

설치

개요

제작자가 쓴 설명(영어 원문)

Amazon Ads API MCP server for Amazon Advertising API

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

사용자 의견i아직 리뷰가 없어요리뷰는 다음 단계에서 계정 기능과 함께 열려요
우리의 기본 점검i1개 중 0개 통과공개된 정보로 점검했으며, 코드는 아직 스캔하지 않았어요
사용 정도i아직 측정 안 함★ –

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

연결 방식: 내 컴퓨터에서 실행
전송 방식: stdio
카테고리: 마케팅 및 소셜 미디어
입력해야 할 값: AMAZON_AD_API_CLIENT_SECRET, AMAZON_AD_API_REFRESH_TOKEN, OPENBRIDGE_REFRESH_TOKEN, OPENBRIDGE_API_KEY, AMAZON_ADS_DOWNLOAD_AUTH_TOKEN

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

기본 점검: 1개 중 0개 통과
내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
직접 입력할 값: AMAZON_ADS_AUTH_METHOD, AMAZON_AD_API_CLIENT_ID, AMAZON_AD_API_CLIENT_SECRET, AMAZON_AD_API_REFRESH_TOKEN, AMAZON_AD_API_PROFILE_ID, OPENBRIDGE_REFRESH_TOKEN, OPENBRIDGE_API_KEY, OPENBRIDGE_REMOTE_IDENTITY_ID, AMAZON_ADS_REGION, AMAZON_AD_API_PACKAGES, AMAZON_ADS_DOWNLOAD_AUTH_TOKEN

비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.

필요한 것

PyPIPython의 uv 설치(uvx 명령어용)

어떤 앱을 쓰세요?

ClaudeClaude CodeCursorVS CodeChatGPT

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "amazon-ads": {
      "command": "uvx",
      "args": [
        "amazon-ads-mcp"
      ],
      "env": {
        "AMAZON_ADS_AUTH_METHOD": "your-value",
        "AMAZON_AD_API_CLIENT_ID": "your-value",
        "AMAZON_AD_API_CLIENT_SECRET": "your-value",
        "AMAZON_AD_API_REFRESH_TOKEN": "your-value",
        "AMAZON_AD_API_PROFILE_ID": "your-value",
        "OPENBRIDGE_REFRESH_TOKEN": "your-value",
        "OPENBRIDGE_API_KEY": "your-value",
        "OPENBRIDGE_REMOTE_IDENTITY_ID": "your-value",
        "AMAZON_ADS_REGION": "your-value",
        "AMAZON_AD_API_PACKAGES": "your-value",
        "AMAZON_ADS_DOWNLOAD_AUTH_TOKEN": "your-value"
      }
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add amazon-ads --env AMAZON_ADS_AUTH_METHOD=your-value --env AMAZON_AD_API_CLIENT_ID=your-value --env AMAZON_AD_API_CLIENT_SECRET=your-value --env AMAZON_AD_API_REFRESH_TOKEN=your-value --env AMAZON_AD_API_PROFILE_ID=your-value --env OPENBRIDGE_REFRESH_TOKEN=your-value --env OPENBRIDGE_API_KEY=your-value --env OPENBRIDGE_REMOTE_IDENTITY_ID=your-value --env AMAZON_ADS_REGION=your-value --env AMAZON_AD_API_PACKAGES=your-value --env AMAZON_ADS_DOWNLOAD_AUTH_TOKEN=your-value -- uvx amazon-ads-mcp

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "amazon-ads": {
      "command": "uvx",
      "args": [
        "amazon-ads-mcp"
      ],
      "env": {
        "AMAZON_ADS_AUTH_METHOD": "your-value",
        "AMAZON_AD_API_CLIENT_ID": "your-value",
        "AMAZON_AD_API_CLIENT_SECRET": "your-value",
        "AMAZON_AD_API_REFRESH_TOKEN": "your-value",
        "AMAZON_AD_API_PROFILE_ID": "your-value",
        "OPENBRIDGE_REFRESH_TOKEN": "your-value",
        "OPENBRIDGE_API_KEY": "your-value",
        "OPENBRIDGE_REMOTE_IDENTITY_ID": "your-value",
        "AMAZON_ADS_REGION": "your-value",
        "AMAZON_AD_API_PACKAGES": "your-value",
        "AMAZON_ADS_DOWNLOAD_AUTH_TOKEN": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "amazon-ads": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "amazon-ads-mcp"
      ],
      "env": {
        "AMAZON_ADS_AUTH_METHOD": "your-value",
        "AMAZON_AD_API_CLIENT_ID": "your-value",
        "AMAZON_AD_API_CLIENT_SECRET": "your-value",
        "AMAZON_AD_API_REFRESH_TOKEN": "your-value",
        "AMAZON_AD_API_PROFILE_ID": "your-value",
        "OPENBRIDGE_REFRESH_TOKEN": "your-value",
        "OPENBRIDGE_API_KEY": "your-value",
        "OPENBRIDGE_REMOTE_IDENTITY_ID": "your-value",
        "AMAZON_ADS_REGION": "your-value",
        "AMAZON_AD_API_PACKAGES": "your-value",
        "AMAZON_ADS_DOWNLOAD_AUTH_TOKEN": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

AMAZON_ADS_AUTH_METHOD env
Authentication method: direct or openbridge.
AMAZON_AD_API_CLIENT_ID env
Amazon Ads API client ID for direct auth.
AMAZON_AD_API_CLIENT_SECRET 비밀 env
Amazon Ads API client secret for direct auth.
AMAZON_AD_API_REFRESH_TOKEN 비밀 env
Amazon Ads API refresh token for direct auth.
AMAZON_AD_API_PROFILE_ID env
Amazon Ads profile ID for direct auth.
OPENBRIDGE_REFRESH_TOKEN 비밀 env
Openbridge refresh token (API key).
OPENBRIDGE_API_KEY 비밀 env
Openbridge API key (alias for OPENBRIDGE_REFRESH_TOKEN).
OPENBRIDGE_REMOTE_IDENTITY_ID env
Openbridge remote identity ID.
AMAZON_ADS_REGION env
Amazon Ads API region (na/eu/fe).
AMAZON_AD_API_PACKAGES env
Comma-separated API packages to load.
AMAZON_ADS_DOWNLOAD_AUTH_TOKEN 비밀 env
Optional bearer token to protect download routes.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

! 주의
제작자와 저장소 일치
게시자(tspicer)가 저장소 소유자(KuudoAI)가 아니에요. 다른 사람이 등록했을 수 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
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
– 해당 없음
OAuth로 로그인
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
… 아직 점검 안 함
도구 설명에 숨겨진 지시 없음
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

마케팅 및 소셜 미디어 카테고리의 다른 서버와 비교i

이 카테고리의 다른 서버 2984개 중 0%보다 스타가 많아요
이 카테고리의 다른 서버 2984개 중 1%보다 최근에 레지스트리에 공개됐어요
기본 점검 결과가 이 카테고리의 다른 서버 2984개 중 37%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 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

입력해야 할 값: AMAZON_AD_API_CLIENT_SECRET, AMAZON_AD_API_REFRESH_TOKEN, OPENBRIDGE_REFRESH_TOKEN, OPENBRIDGE_API_KEY, AMAZON_ADS_DOWNLOAD_AUTH_TOKEN

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.4)은 9개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.

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:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

MCP YouTube Transcript

제작자: jkawamoto

An MCP server retrieving transcripts of YouTube videos

내 컴퓨터에서 실행★ 495MIT10일 전 업데이트

설치

Google Analytics MCP

제작자: surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

내 컴퓨터에서 실행★ 244MIT10일 전 업데이트

설치

BibiGPT YouTube Video Summarizer

제작자: JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

클라우드에서 실행★ 137MIT10일 전 업데이트

설치

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

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-mcp
cp .env.example .env and add credentials (see Configuration).
`docker compos

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

Amazon Ads MCP

개요

PopNx MCP의 세 기둥

할 수 있는 일

설치

설치하기 전에

직접 입력할 값

할 수 있는 일

기본 점검i

제작자와 저장소 일치

계속 관리되고 있음

라이선스 있음

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Kuudo Amazon Ads MCP Server

Table of contents

Questions this server answers

Which MCP server connects Claude or ChatGPT to Amazon Ads, including DSP and Amazon Marketing Cloud?

Can I self-host an Amazon Ads MCP server in my own AWS or GCP account?

Does it cover Seller Central and Vendor Central too?

Can an agency run it across many client accounts?

How is it different from Amazon's own Ads MCP Server?

Where this fits in Kuudo

What Are MCP Tools?

🚀 What is Amazon Ads API MCP SDK?

✨ Key Features

🎯 Use Cases

Claude Desktop Integration

AI Applications

Enterprise Services

Developer Tools

Why this Ads MCP is different

You've felt this before

Here, the wrong moves return the right move

Everything is an edge case, you can help

Quick start