# Apple App Store Reviews & App Metadata Scraper (`captainhandsome/app-store-reviews-search`) Actor

Search the Apple App Store and extract app metadata plus customer reviews with ratings, versions and dates, across any App Store country - no API key required.

- **URL**: https://apify.com/captainhandsome/app-store-reviews-search.md
- **Developed by:** [Joseph McRell](https://apify.com/captainhandsome) (community)
- **Categories:** E-commerce, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.28 / 1,000 result rows

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 & App Metadata Scraper

Extract Apple App Store customer reviews and app metadata for one app or a batch, from any App Store storefront. Every record is a flat, CSV-ready row of 42 columns, and every review row carries its app's identity so a single export needs no joining.

Pairs with [Google Play Reviews Scraper](https://apify.com/captainhandsome/google-play-reviews-scraper): the two Actors emit the same shape of row, so one run each gives you iOS and Android feedback side by side.

### What data can I extract?

**Per review**

- Apple's review ID, star rating, title and full body text
- Reviewer nickname and profile URL
- The app version the review was written against, and the post/edit timestamp
- Helpful-vote sum and total vote count
- The storefront the review came from

**Per app** (always attached to each review row, and emitted on its own when `include_reviews` is off)

- Track ID, bundle ID, app name and canonical store URL
- Developer name, developer ID and developer page
- Primary category and the full category list
- Price and currency
- Lifetime average rating and rating count, plus current-version rating and count
- Current version string, first release date, and current-version release date
- Download size, minimum iOS version, supported-device count
- Content advisory rating, description, What's New notes, icon URL, screenshot count
- Supported languages and the developer's own website

### Input example

```json
{
  "search_query": "language learning",
  "countries": ["us", "gb"],
  "include_reviews": true,
  "max_reviews_per_app": 100,
  "max_items": 200
}
```

Target specific apps instead of searching by passing `app_ids` — numeric track IDs (`570060128`), bundle IDs (`com.duolingo.DuolingoMobile`) or App Store URLs, whichever you already have:

```json
{
  "app_ids": ["570060128", "https://apps.apple.com/us/app/id284882215"],
  "countries": ["us"],
  "max_reviews_per_app": 200
}
```

### Reviews are per storefront

Apple keeps a separate review feed for every country, so the `us` and `gb` feeds hold different reviews for the same app. Listing several `countries` multiplies coverage rather than repeating it, and rows are deduplicated per storefront by Apple's review ID.

The public review feed serves 50 reviews per page and stops at page 10, so **500 reviews per app per storefront** is Apple's ceiling, not ours. Ask for more coverage by adding storefronts.

### Filtering, before you are billed

`min_rating`, `max_rating` and `recent_days` are applied before any row is pushed, so a filtered-out review never appears on your bill:

- `{"min_rating": 4}` — testimonials and positive quotes
- `{"max_rating": 2}` — complaint mining and churn reasons
- `{"recent_days": 30}` — what changed since the last release

### Typical uses

- Track sentiment across a version release and see which build the complaints attach to
- Compare your ratings with competitors in the same category, in several countries at once
- Mine one and two-star reviews for feature requests and defect reports
- Pull app metadata in bulk for market maps and ASO research
- Diff iOS against Android feedback for the same product

### Output example

```json
{
  "record_type": "review",
  "app_id": "570060128",
  "app_bundle_id": "com.duolingo.DuolingoMobile",
  "app_name": "Duolingo: Language Lessons",
  "app_url": "https://apps.apple.com/us/app/duolingo-language-lessons/id570060128",
  "country": "us",
  "developer": "Duolingo, Inc",
  "primary_genre": "Education",
  "price": 0,
  "currency": "USD",
  "app_average_rating": 4.72323,
  "app_rating_count": 5454005,
  "app_version": "7.140.0",
  "app_updated": "2026-09-14T15:53:43Z",
  "review_id": "14561009045",
  "review_title": "Enjoying the format and the teaching process",
  "review_body": "Three months in and the streak is the only reason I have kept at anything this long.",
  "review_rating": 5,
  "review_author": "Hapagirl8",
  "review_version": "7.140.0",
  "review_updated": "2026-09-17T09:27:36-07:00",
  "review_vote_sum": 0,
  "review_vote_count": 0,
  "fetched_at": "2026-09-18T21:44:02Z"
}
```

### Common use cases

- **Release triage.** Pull the reviews attached to the version you shipped this week and read the complaints by build.
- **Competitor tracking.** Search a category, take the top apps, and compare rating trajectories across storefronts.
- **Voice of the customer.** Mine one and two-star bodies for the phrases that repeat, then feed them to your backlog.
- **Market maps.** Metadata-only runs return one row per app: category, price, size, ratings and release cadence.
- **Cross-platform view.** Run this with the Google Play Actor for the same product and compare iOS to Android.

### Use with AI agents and MCP

This Actor is exposed as an MCP tool, so an agent can call it directly. Example agent intent:

> Get the 100 most recent one and two-star Duolingo reviews from the UK and US stores, with the app version each one was written against.

```json
{
  "app_ids": ["570060128"],
  "countries": ["gb", "us"],
  "max_rating": 2,
  "max_reviews_per_app": 50,
  "max_items": 100
}
```

### Reliability

Apple's public search, lookup and review endpoints are used directly - no browser, no proxy, no API key, so there is no anti-bot surface to drift. Requests retry with backoff on throttling and transport errors, reviews are deduplicated per storefront by Apple's review ID, and an app that returns no reviews in a storefront still yields its metadata row rather than an empty result. Rating and date filters run before rows are pushed, so a filtered row is never billed.

### Limitations and responsible use

- Public App Store data only.
- Apple's public review feed serves 50 reviews per page and stops at 10 pages, so 500 reviews per app per storefront is the ceiling. Add storefronts for more coverage.
- Reviews differ per country; a review visible in the US feed may be absent from the GB feed.
- Apple does not expose developer replies in the public feed, so there is no reply column here.
- App-level columns describe the app at run time, not at the time each review was written. Ratings, prices and versions change.
- Review timestamps are returned as Apple reports them, including the storefront's UTC offset.
- Use public review data in accordance with applicable law and platform terms.

### FAQ

**Do I need an Apple developer account or API key?** No. Every endpoint used here is public.

**Can I get more than 500 reviews for one app?** Not from one storefront - that is Apple's limit. Query several countries to widen coverage.

**Can I look up an app by its App Store link?** Yes. `app_ids` accepts numeric track IDs, bundle IDs and full App Store URLs.

**Why did I get an app row instead of reviews?** Either `include_reviews` was off, or that app has no reviews in the storefront you queried.

**Does it cover the Mac App Store?** The search and lookup calls target iOS software. Mac-only titles are out of scope.

### Pricing and cost control

Output is billed per result at **$0.0004 per result** (about $0.40 per 1,000 results), plus a $0.0005 Actor-start charge billed once per gigabyte of memory at run start. Use `max_items` to cap both output volume and charges. The price shown on the Apify Store listing is authoritative.

`max_items` caps the total rows a run can return and bill; `max_reviews_per_app` caps each app's share. A metadata-only run (`include_reviews: false`) returns one row per app and is the cheapest way to survey a category.

### Notes and limits

- No API key, browser or proxy is needed; the Actor uses Apple's own public search, lookup and review-feed endpoints.
- Apple does not expose developer replies in the public review feed. That column exists only on the Google Play Actor.
- An app with no reviews in a storefront still returns its metadata row rather than nothing.
- Review timestamps are returned exactly as Apple reports them, including the storefront's UTC offset.

# Changelog

This Actor's version history is a separate document: https://apify.com/captainhandsome/app-store-reviews-search/changelog.md

# Actor input Schema

## `search_query` (type: `string`):

Find apps by name or keyword, exactly as you would in App Store search. Leave empty when you supply app IDs or URLs instead.

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

Specific apps to collect, as numeric track IDs (570060128), bundle IDs (com.duolingo.DuolingoMobile) or App Store URLs. Overrides the search term when present.

## `countries` (type: `array`):

Two-letter App Store country codes to collect from, for example us, gb, de. Reviews differ per storefront. Defaults to us.

## `include_reviews` (type: `boolean`):

Collect customer reviews as well as app metadata. Turn off for a fast metadata-only run.

## `max_reviews_per_app` (type: `integer`):

Upper bound on reviews collected per app per storefront. Apple serves 50 per page and caps the public feed at 10 pages, so 500 per storefront is the ceiling.

## `min_rating` (type: `integer`):

Keep only reviews at or above this rating, for example 4 for positive reviews. Leave empty to keep every rating.

## `max_rating` (type: `integer`):

Keep only reviews at or below this rating, for example 2 to study complaints. Defaults to 5, which keeps every rating.

## `recent_days` (type: `integer`):

Keep only reviews posted within this many days, for example 30 for the last month. Leave empty for the whole feed.

## `max_items` (type: `integer`):

Total rows to return and bill across every app and storefront. Defaults to 100.

## Actor input object example

```json
{
  "search_query": "language learning",
  "countries": [
    "us"
  ],
  "include_reviews": true,
  "max_reviews_per_app": 100,
  "max_rating": 5,
  "max_items": 100
}
```

# Actor output Schema

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

One flat record per review, or per app in metadata mode.

# 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 = {
    "search_query": "language learning"
};

// Run the Actor and wait for it to finish
const run = await client.actor("captainhandsome/app-store-reviews-search").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 = { "search_query": "language learning" }

# Run the Actor and wait for it to finish
run = client.actor("captainhandsome/app-store-reviews-search").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 '{
  "search_query": "language learning"
}' |
apify call captainhandsome/app-store-reviews-search --silent --output-dataset

```

## MCP server setup

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

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/uE6wrbvbw6XWPk3lt/builds/OYsCwEjkJUD0kcUJS/openapi.json