# Amazon Reviews & Customers Say Scraper (`metqo/amazon-public-reviews`) Actor

Top reviews from Amazon's public product pages across up to 12 marketplaces (merged and deduplicated), plus the 'Customers say' AI summary and topic sentiment, rating histogram and product details. No login, no cookies. Honest limits; failed products are never charged.

- **URL**: https://apify.com/metqo/amazon-public-reviews.md
- **Developed by:** [Tanusree Halder](https://apify.com/metqo) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 reviews

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Amazon Reviews & "Customers Say" Scraper — public pages, no login

Reviews and Amazon's AI **"Customers say"** summary from public product pages, across up to 12 marketplaces, merged and deduplicated. No login, no cookies, no accounts. **Products that fail or get blocked are never charged.**

### What you get, stated plainly

Amazon shows **about 8–13 reviews per product per marketplace** without signing in. That's a hard limit, and it applies to every public-page scraper. This actor gets more **legitimately**:

- **Multi-marketplace merge:** US + CA + AU etc. Each country's page adds its own top reviews; duplicates are removed. Tested: one product returned 20 unique reviews from US + CA + AU.
- **"Customers say" topics:** each topic (e.g. *comfort*, *fit*, *sound quality*) with **positive / negative / mixed** sentiment, mention counts, and Amazon's one-line summary. This summarises **all** of a product's reviews, not just the ones shown.
- **Product details:** price, list price, availability, rating, rating count, star histogram (%).
- **An honest summary row per product:** which marketplaces worked, how many reviews were on the pages, how many you received.

Not possible without sign-in, so not offered: full review lists, "all 1★ reviews", date sorting. Public pages show mostly *top* (often positive) reviews, so a 1–2★ filter may return only a few; use the "Customers say" negative topics for complaints.

### Switching from another Amazon reviews scraper?

Paste your existing input: `productUrls` (strings or `{ "url": ... }`), `asins`, `maxReviews` and `includeGdprSensitive` are understood as-is.

### Input

```json
{
  "products": ["B09B8V1LZ3", "https://www.amazon.com/dp/B0DYHY9B6M"],
  "marketplaces": ["US", "CA", "AU"],
  "stars": [],
  "verifiedOnly": false,
  "keywords": []
}
```

Marketplaces: US, CA, UK, DE, FR, IT, ES, IN, AU, AE, SA, JP. Each is fetched through a proxy in that country.

### Output (one dataset; `recordType` = `product`, `review` or `summary`)

```json
{"recordType": "review", "asin": "B09B8V1LZ3", "marketplace": "US", "reviewId": "R3N0H8AJQZM3P0",
 "rating": 4, "title": "Sweet little device, but a tad hard of hearing",
 "text": "I bought this little guy for my kitchen and over all, love it...",
 "submittedAt": "2026-09-21", "reviewedIn": "United States", "verifiedPurchase": true,
 "variant": "Color: Deep Sea Blue Size: Pack of 1 Configuration: Device only", "helpfulVotes": 3,
 "url": "https://www.amazon.com/gp/customer-reviews/R3N0H8AJQZM3P0"}
```

```json
{"recordType": "product", "asin": "B09B8V1LZ3", "marketplace": "US", "price": 39.99, "wasPrice": 79.99,
 "availability": "In Stock", "averageRating": 4.7, "ratingCount": 200201,
 "ratingHistogramPercent": {"5": 82, "4": 11, "3": 3, "2": 1, "1": 3},
 "customersSay": "Customers find the Echo Dot to be fantastic...",
 "topics": [{"topic": "quality", "sentiment": "positive", "mentions": 6392, "summary": "Customers find the Echo Dot to be fantastic..."}]}
```

### Pricing

**$0.004 per product page** (includes "Customers say" and details) and **$0.002 per review**. Failed or blocked marketplaces and summary rows are free. Typical cost: 1 product × 3 marketplaces ≈ 3 × $0.004 + ~25 reviews × $0.002 ≈ **$0.06**.

### Use it from Claude, Cursor or other AI assistants (MCP)

Your AI assistant can call this scraper directly and pay per result like any other run. Add Apify's MCP server with the Metqo tools:

```
https://mcp.apify.com?tools=metqo/walmart-product-reviews,metqo/amazon-public-reviews
```

- **Claude** (desktop or claude.ai): Settings → Connectors → *Add custom connector* → paste the URL → sign in to Apify.
- **Cursor / VS Code:** add to your MCP config:

```json
{ "mcpServers": { "metqo": { "url": "https://mcp.apify.com?tools=metqo/walmart-product-reviews,metqo/amazon-public-reviews" } } }
```

Then just ask, e.g. *"What do verified buyers complain about most for Walmart item 10450114? Group by topic."*

### More from Metqo Data

- **[Walmart Product & Reviews Scraper](https://apify.com/metqo/walmart-product-reviews)**: every Walmart review (not just the top ones) with verified, star, date, keyword and topic-sentiment filters, plus monitoring mode.
- Need scheduled feeds or other retailers? **support@metqo.com**

# Actor input Schema

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

Product IDs or URLs to scrape.

## `marketplaces` (type: `array`):

Each marketplace adds its own top reviews (merged, deduplicated). Options: US, CA, UK, DE, FR, IT, ES, IN, AU, AE, SA, JP.

## `scrapeProductDetails` (type: `boolean`):

Also return one product-details record per product.

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

Amazon shows about 8-13 reviews per marketplace without sign-in; this is a cap, not a promise.

## `stars` (type: `array`):

Only reviews with these star ratings, e.g. \[1, 2]. Empty = all.

## `verifiedOnly` (type: `boolean`):

Only reviews from verified purchases.

## `keywords` (type: `array`):

Keep only reviews whose title or text contains any of these words (case-insensitive).

## `includePersonalInfo` (type: `boolean`):

Enable only with a lawful basis under GDPR/CCPA.

## `maxAgeHours` (type: `integer`):

Data fetched by anyone in the last N hours may be returned instantly from our cache (same price, faster, each row marked fromCache). 0 = always fetch live.

## `maxConcurrency` (type: `integer`):

How many products to process in parallel.

## `proxyConfiguration` (type: `object`):

Proxy.

## Actor input object example

```json
{
  "products": [
    "B00FLYWNYQ"
  ],
  "marketplaces": [
    "US"
  ],
  "scrapeProductDetails": true,
  "maxReviewsPerProduct": 100,
  "stars": [],
  "verifiedOnly": false,
  "includePersonalInfo": false,
  "maxAgeHours": 24,
  "maxConcurrency": 2,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

Every record: products, reviews and the per-item run summary (field recordType tells them apart).

## `products` (type: `string`):

One record per product and marketplace: price, availability, rating histogram, Customers say topics.

## `reviews` (type: `string`):

Top reviews merged across marketplaces, deduplicated.

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

Per ASIN: which marketplaces worked and how many reviews were delivered.

# 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": [
        "B00FLYWNYQ"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("metqo/amazon-public-reviews").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": ["B00FLYWNYQ"] }

# Run the Actor and wait for it to finish
run = client.actor("metqo/amazon-public-reviews").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": [
    "B00FLYWNYQ"
  ]
}' |
apify call metqo/amazon-public-reviews --silent --output-dataset

```

## MCP server setup

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

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/tAFgD1tktNa7vZL5t/builds/qBnobmx2XygkgOSv6/openapi.json