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Amazon Ads MCP

by KuudoAIversion 0.2.4i★ –iRuns on your computer
Registry nameio.github.tspicer/amazon_ads_mcp

Install

Overview

Description from the maker (original English)

Amazon Ads API MCP server for Amazon Advertising API

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Marketing & social media
  • You need to fill in: AMAZON_AD_API_CLIENT_SECRET, AMAZON_AD_API_REFRESH_TOKEN, OPENBRIDGE_REFRESH_TOKEN, OPENBRIDGE_API_KEY, AMAZON_ADS_DOWNLOAD_AUTH_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 0 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: 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

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "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"
      }
    }
  }
}

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • 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 secret env
    Amazon Ads API client secret for direct auth.
  • AMAZON_AD_API_REFRESH_TOKEN secret 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 secret env
    Openbridge refresh token (API key).
  • OPENBRIDGE_API_KEY secret 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 secret env
    Optional bearer token to protect download routes.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ! Caution

    Maker matches the repo

    The publisher (tspicer) is not the repo owner (KuudoAI); someone else may have listed it

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

  • More stars than 0% of the other 2990 servers in this category
  • Published to the registry more recently than 1% of the other 2990 servers in this category
  • Basic checks equal to or better than 33% of the other 2990 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Amazon Ads MCP safe?

It passed 0 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: AMAZON_AD_API_CLIENT_SECRET, AMAZON_AD_API_REFRESH_TOKEN, OPENBRIDGE_REFRESH_TOKEN, OPENBRIDGE_API_KEY, AMAZON_ADS_DOWNLOAD_AUTH_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.4) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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.

LayerWhat it providesWhere
MCP serversThe tools an agent calls: Amazon Ads here, plus Selling Partner and Vendor Centralthis repo, and the MCP tool reference
SkillsThe higher-level workflows: reusable, versioned, multi-step Amazon procedures that compose these tools and wait for a human before anything goes liveAmazon Agent Skills
Agent AtlasThe knowledge: indexed Amazon operating knowledge across Ads, Seller Central, and Vendor Central, answered with citationsAmazon Agent Atlas
Agent FlowThe place to work: your Amazon data landed in your own cloud, so an agent answers with real figures instead of guessingAmazon 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).

  1. git clone https://github.com/KuudoAI/amazon-ads-mcp.git && cd amazon-ads-mcp
  2. cp .env.example .env and add credentials (see Configuration).
  3. `docker compos

Only the beginning is shown; read the rest in the repo

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