# Amazon product data for an n8n or AI agent workflow

**Use case:** 

Call this actor as a step in an n8n scenario or AI agent tool call: paste ASINs, get clean structured product data back. $4 per 1,000.

## Input

```json
{
  "asins": [
    "B0CX23V2ZK",
    "B0BSHF7WHW",
    "B0863TXGM3",
    "B0CHWRXH8B",
    "B0D1XD1ZV3",
    "B09B8V1LZ3",
    "B0BDHB9Y8H",
    "B07XJ8C8F5",
    "B07FZ8S74R",
    "B08N5KWB9H",
    "B08KTZ8249",
    "B09G9FPHY6",
    "B07ZPKN6YR"
  ],
  "marketplace": "com",
  "testRun": false,
  "onlyFound": false,
  "includeKeywords": [],
  "excludeKeywords": [],
  "columns": [
    "asin",
    "marketplace",
    "title",
    "brand",
    "price",
    "currency",
    "currencyMismatch",
    "expectedCurrency",
    "listPrice",
    "rating",
    "reviewCount",
    "availability",
    "bulletPoints",
    "category",
    "imageUrl",
    "bestSellerRankText",
    "productUrl"
  ],
  "maxConcurrency": 3,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

## Output

```json
{
  "query": {
    "label": "ASIN submitted",
    "format": "string"
  },
  "found": {
    "label": "Found?",
    "format": "boolean"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "message": {
    "label": "Details",
    "format": "string"
  },
  "asin": {
    "label": "ASIN",
    "format": "string"
  },
  "marketplace": {
    "label": "Marketplace",
    "format": "string"
  },
  "title": {
    "label": "Product title",
    "format": "string"
  },
  "brand": {
    "label": "Brand",
    "format": "string"
  },
  "price": {
    "label": "Price",
    "format": "number"
  },
  "currency": {
    "label": "Currency",
    "format": "string"
  },
  "currencyMismatch": {
    "label": "Currency mismatch",
    "format": "boolean"
  },
  "expectedCurrency": {
    "label": "Expected currency (marketplace)",
    "format": "string"
  },
  "listPrice": {
    "label": "List price (struck through)",
    "format": "number"
  },
  "rating": {
    "label": "Star rating",
    "format": "number"
  },
  "reviewCount": {
    "label": "Ratings count",
    "format": "number"
  },
  "availability": {
    "label": "Availability",
    "format": "string"
  },
  "bulletPoints": {
    "label": "Feature bullets",
    "format": "array"
  },
  "category": {
    "label": "Category breadcrumb",
    "format": "string"
  },
  "imageUrl": {
    "label": "Main image",
    "format": "string"
  },
  "bestSellerRankText": {
    "label": "Best Sellers Rank",
    "format": "string"
  },
  "productUrl": {
    "label": "Product page",
    "format": "string"
  },
  "scrapedAt": {
    "label": "Checked at",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Amazon Product Scraper: Price, Stock & Rating by ASIN Actor is ready to run with the inputs already set for "Amazon product data for an n8n or AI agent workflow". [Sign up or log in](https://console.apify.com/create-task-from-example/Q1fLawMAcT0W61Z4l) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Amazon product data for an n8n or AI agent workflow" task

The Amazon Product Scraper: Price, Stock & Rating by ASIN Actor will start running based on the input automatically. You can also change all the input fields, like ASINs or Amazon product URLs, which amazon marketplace?, and more, to match your specific use case.

### 3. Receive the "Amazon product data for an n8n or AI agent workflow" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as ASIN submitted, found?, status, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Amazon product data for an n8n or AI agent workflow" task via API](https://apify.com/accountable_eel/amazon-product-lookup.md).

## About this Actor

This example demonstrates how to use [Amazon Product Scraper: Price, Stock & Rating by ASIN](https://apify.com/accountable_eel/amazon-product-lookup.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/accountable_eel/amazon-product-lookup.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/accountable_eel/amazon-product-lookup.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).