# Apple App Store Reviews Scraper — Recent Reviews (`thenetaji/apple-app-store-reviews-scraper`) Actor

Export up to 500 recent public reviews per app and country. Each structured row carries the rating, title, text, author, update date, reviewed app version, and helpful vote count and sum.

- **URL**: https://apify.com/thenetaji/apple-app-store-reviews-scraper.md
- **Developed by:** [The Netaji](https://apify.com/thenetaji) (community)
- **Categories:** Marketing, Developer tools, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.06 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## Apple App Store Reviews Scraper

Export the most recent public App Store reviews for one or many apps, with one dataset row per review. Country is part of the input and the output, so storefront-specific feedback stays explicit.

```json
{
  "app_ids": ["324684580"],
  "country": "US",
  "maxReviews": 100
}
```

App links work alongside numeric IDs. `maxReviews` applies per app and accepts 1–500; two apps at the default can return up to 200 rows.

### Real review row

```json
{
  "app_id": "324684580",
  "country": "US",
  "review_id": "14455499988",
  "author_name": "Marilyn in FL",
  "updated_at": "2026-08-21T09:45:22-07:00",
  "rating": 5,
  "review_version": "9.1.76",
  "review_title": "Spotify Playlists",
  "helpful_vote_count": 0,
  "helpful_vote_sum": 0
}
```

The row can also include `author_url` and the full review `text`. Those fields are null when the review feed omits them.

### Limit that matters

Apple exposes a recent window of at most 500 reviews per app and country here. This is not complete review history. Schedule repeated runs and deduplicate on `review_id` when you need an ongoing monitor. An empty feed succeeds with no rows; it does not establish that the app itself is missing. Developer replies are not part of this review output.

For the aggregate `average_rating` and `rating_count`, use the [apple-app-store-scraper](https://apify.com/thenetaji/apple-app-store-scraper) (`appDetail` mode). To find apps before collecting feedback, start with the [Apple App Store Search Scraper](https://apify.com/thenetaji/apple-app-store-search-scraper).

# Actor input Schema

## `app_ids` (type: `array`):

Numeric App Store IDs or apps.apple.com links. Add one per line; links and IDs can be mixed.

## `country` (type: `string`):

Two-letter App Store storefront code.

## `maxReviews` (type: `integer`):

Maximum recent reviews to save for each app, from 1 to 500.

## Actor input object example

```json
{
  "app_ids": [
    "324684580",
    "https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580"
  ],
  "country": "US",
  "maxReviews": 50
}
```

# Actor output Schema

## `dataset` (type: `string`):

All records scraped by this run

# 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 = {
    "app_ids": [
        "324684580"
    ],
    "country": "US",
    "maxReviews": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("thenetaji/apple-app-store-reviews-scraper").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 = {
    "app_ids": ["324684580"],
    "country": "US",
    "maxReviews": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("thenetaji/apple-app-store-reviews-scraper").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 '{
  "app_ids": [
    "324684580"
  ],
  "country": "US",
  "maxReviews": 50
}' |
apify call thenetaji/apple-app-store-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thenetaji/apple-app-store-reviews-scraper"
        }
    }
}
```

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/Hmbudf8aV9cPZuuMP/builds/McFpEA4JssF7RcZEk/openapi.json