# Amazon Reviews Scraper API (`antonio_cesar/amazon-reviews-scraper-api`) Actor

Collect live Amazon.com product reviews for sentiment analysis, product research, quality monitoring, and customer feedback workflows.

- **URL**: https://apify.com/antonio\_cesar/amazon-reviews-scraper-api.md
- **Developed by:** [Antônio César](https://apify.com/antonio_cesar) (community)
- **Categories:** E-commerce, Developer tools, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.00 / 1,000 amazon results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### What does Amazon Reviews Scraper API do?

**Amazon Reviews Scraper API** collects live Amazon.com product reviews as structured records for sentiment analysis, product research, quality monitoring, and customer-feedback workflows. It extracts review identifiers, titles, text, ratings, purchase verification, product context, and collection timestamps while excluding reviewer identity by default.

Use it in the Apify Console or API, schedule recurring collections, and deliver results to webhooks, Make, Zapier, Google Sheets, databases, or NLP pipelines. Managed data infrastructure handles the external collection job; users do not need browsers, proxies, or a separate data-provider account.

### Why use Amazon Reviews Scraper API?

Review content can reveal recurring complaints, desired features, product-positioning opportunities, and changes in perceived quality. The Actor provides a privacy-conscious normalized contract and lets incremental workflows exclude review IDs already collected. Reviewer names and profile identifiers require an explicit opt-in.

### How to scrape Amazon reviews

1. Click **Try for free**.
2. Enter up to 100 Amazon.com product URLs or ASINs.
3. Choose the maximum reviews per product.
4. Optionally enter review IDs that should not be returned again.
5. Start the run and open the **Reviews** dataset view.

### Input

```json
{
  "products": ["B0CRMZHDG8"],
  "maxReviewsPerProduct": 20,
  "excludeReviewIds": ["R123ALREADYSEEN"],
  "includeReviewerIdentity": false,
  "includeRawData": false
}
```

The limit is per product: 100 products with 100 reviews can produce up to 10,000 billable records for every user.

### Output

```json
{
  "recordType": "reviews",
  "input": "B0CRMZHDG8",
  "asin": "B0CRMZHDG8",
  "reviewId": "R123EXAMPLE",
  "reviewTitle": "Works as expected",
  "reviewText": "The product was easy to use.",
  "rating": 5,
  "verifiedPurchase": true,
  "marketplace": "https://www.amazon.com",
  "sourceUrl": "https://www.amazon.com/dp/B0CRMZHDG8",
  "scrapedAt": "2026-08-21T12:00:00Z"
}
```

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

### Data table

| Field | Meaning |
|---|---|
| `asin`, `sourceUrl` | Reviewed product |
| `reviewId` | Stable review identifier when available |
| `reviewTitle`, `reviewText` | Review content |
| `rating` | Normalized numeric rating |
| `verifiedPurchase` | Amazon verification flag |
| `scrapedAt` | UTC collection timestamp |

### How much does it cost to scrape Amazon reviews?

The PPE price is **US$0.008 per delivered review**, or **US$8 per 1,000 reviews**. Five reviews cost US$0.04 and 100 cost US$0.80. The standard US$0.00005 Actor-start event applies per applicable start unit; platform usage is included.

### Tips and advanced options

Start with 20 reviews per product and increase only after checking coverage. Store `reviewId` values and pass them back through `excludeReviewIds` for incremental collection. Keep identity and raw data disabled unless they are necessary. Enabling reviewer identity means you are responsible for establishing a lawful purpose and legal basis.

### FAQ, disclaimers, and support

This Actor currently supports Amazon.com reviews. Amazon may expose fewer reviews than requested, and availability can vary. **Unofficial — not affiliated with or endorsed by Amazon.** Follow applicable privacy law, Amazon terms, and intellectual-property rules. Open the Actor **Issues** tab for support or custom sentiment workflows.

For products, search, Best Sellers, and sellers, use [Amazon Data Suite](https://apify.com/antonio_cesar/amazon-data-suite).

# Actor input Schema

## `products` (type: `array`):

Enter 1–100 ASINs or Amazon.com product URLs.

## `maxReviewsPerProduct` (type: `integer`):

Maximum reviews for each product. 100 products × 100 reviews can produce 10,000 billable records.

## `excludeReviewIds` (type: `array`):

Optional review IDs already collected. They are applied to every requested product.

## `includeReviewerIdentity` (type: `boolean`):

Off by default. Enable only if you have a lawful purpose and legal basis for processing reviewer names or profile identifiers.

## `includeRawData` (type: `boolean`):

Add provider fields under rawData. Identity fields remain removed unless the identity option is also enabled.

## Actor input object example

```json
{
  "products": [
    "B0CRMZHDG8"
  ],
  "maxReviewsPerProduct": 20,
  "excludeReviewIds": [],
  "includeReviewerIdentity": false,
  "includeRawData": false
}
```

# Actor output Schema

## `results` (type: `string`):

Successful normalized Amazon records. Validation and upstream errors are never mixed into this billable dataset.

## `summary` (type: `string`):

Live or final run status with requested, successful, failed, and charged counts.

## `errors` (type: `string`):

Structured validation or upstream errors, kept outside the results dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "products": [
        "B0CRMZHDG8"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("antonio_cesar/amazon-reviews-scraper-api").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "products": ["B0CRMZHDG8"] }

# Run the Actor and wait for it to finish
run = client.actor("antonio_cesar/amazon-reviews-scraper-api").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "products": [
    "B0CRMZHDG8"
  ]
}' |
apify call antonio_cesar/amazon-reviews-scraper-api --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,antonio_cesar/amazon-reviews-scraper-api"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/c59kL5a3EpMoWmuoV/builds/IXDiS1zLVbNiIUsyR/openapi.json