MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Amazon Ads API MCP server for Amazon Advertising API
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
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_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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-mcpFill in the empty values before running it.
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.
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.
AMAZON_ADS_AUTH_METHOD envAMAZON_AD_API_CLIENT_ID envAMAZON_AD_API_PROFILE_ID envOPENBRIDGE_REMOTE_IDENTITY_ID envAMAZON_ADS_REGION envAMAZON_AD_API_PACKAGES envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The publisher (tspicer) is not the repo owner (KuudoAI); someone else may have listed it
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
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
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).
The GitHub repo last changed –, and the latest version (0.2.4) reached the registry 9 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
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.
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
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.
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.
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.
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.
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.
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.
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:
👉 In short: MCP tools = a safe, well-labeled toolkit that lets AI work with the Amazon Ads API.
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.
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 know the symptoms even if you've never thought of them as a single problem:
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.
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.
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.
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.
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 .env and add credentials (see Configuration).Only the beginning is shown; read the rest in the repo