# App Store Reviews Scraper API (`steady-data/app-store-reviews-scraper`) Actor

Scrape iOS App Store reviews for any iPhone or iPad app and export to CSV, Excel or JSON, or use it as an App Store reviews API. Rating, title, text, version, date and votes by country. No login, no proxy. $0.10 per 1,000 reviews.

- **URL**: https://apify.com/steady-data/app-store-reviews-scraper.md
- **Developed by:** [Steady Data](https://apify.com/steady-data) (community)
- **Categories:** Developer tools, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.10 / 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

## App Store Reviews Scraper API

Scrape iOS App Store reviews for any iPhone or iPad app and export them to CSV, Excel or JSON, or call it as an App Store reviews API from Python, JavaScript, n8n, Zapier or an AI agent. Each row is one review: star rating, title, text, app version, date, vote count and the reviewer's public nickname. **$0.10 per 1,000 reviews**, and apps with no reviews cost nothing.

It reads Apple's own public customer reviews feed and the iTunes Lookup API. No Apple account, no browser, no proxy.

**Contents:** [Who uses it](#who-uses-it) · [Input](#input) · [More than 500](#need-more-than-500-reviews) · [Examples](#input-examples) · [Output fields](#output-fields) · [Export](#export-to-csv-or-excel) · [API](#use-it-as-an-app-store-reviews-api) · [AI agents (MCP)](#use-it-from-ai-agents-mcp) · [Pricing](#pricing) · [Limits](#limits) · [FAQ](#faq)

### Who uses it

- **Product managers and app developers** read what changed after each release. Filter by `version`, or pull only 1- and 2-star reviews to find bugs and feature requests.
- **ASO and app marketing teams** compare a client's app with competitors, country by country, and track how ratings move.
- **Analysts and data teams** feed reviews into sentiment analysis, topic models, dashboards or an LLM summary.
- **Support teams** watch new low-star reviews on a schedule and route them to a queue.

It works for any public app, not just your own, so you don't need App Store Connect access.

### Input

Give apps as App Store links, numeric app IDs or plain names. A name is matched to the top App Store search result, and the run log says which app it picked.

| Field | What it does |
|---|---|
| `apps` | Required. App Store URLs, IDs (`389801252` or `id389801252`) or names. |
| `countries` | Two-letter store codes, e.g. `us`, `gb`, `de`, `jp`. Default `us`. Use `all` for every storefront (about 155). |
| `sort` | `mostrecent` (default) or `mosthelpful`. |
| `maxReviewsPerApp` | Cap per app, across all countries. Default 500. |
| `since` | With `mostrecent`, stops once reviews are older than this date (`YYYY-MM-DD`). |
| `minRating` / `maxRating` | Keep only reviews in this star range. Reviews you filter out are not charged. |
| `includeAppDetails` | Adds app name, developer, genre, average rating, rating count, price and current version to each row. Free. |

### Need more than 500 reviews?

Apple's public feed gives at most 500 reviews per app, per country, per sort order. To get more, set `countries` to `all`: the actor then goes through all 155 App Store storefronts. Popular apps can return several thousand reviews this way, and you also see how the app is received in each market. Add `"sort": "mosthelpful"` in a second run for a different slice of reviews.

```json
{ "apps": ["389801252"], "countries": ["all"], "maxReviewsPerApp": 20000 }
```

### Input examples

**Latest reviews for one app**

```json
{ "apps": ["https://apps.apple.com/us/app/instagram/id389801252"] }
```

**Complaints only since a date, US and UK**

```json
{
  "apps": ["duolingo"],
  "countries": ["us", "gb"],
  "since": "2026-10-01",
  "maxRating": 2
}
```

**Competitor sweep across three apps**

```json
{
  "apps": ["spotify", "389801252", "https://apps.apple.com/us/app/tidal-music/id913943275"],
  "countries": ["us"],
  "maxReviewsPerApp": 300
}
```

**Compare how one app is received in different countries**

```json
{
  "apps": ["570060128"],
  "countries": ["us", "de", "fr", "jp", "br"],
  "sort": "mosthelpful",
  "maxReviewsPerApp": 1000
}
```

### Output fields

One dataset item per review:

```json
{
  "appId": "570060128",
  "appName": "Duolingo: Learn Languages",
  "developer": "Duolingo",
  "genre": "Education",
  "averageRating": 4.72,
  "ratingCount": 5506852,
  "currentVersion": "7.144.0",
  "country": "us",
  "sort": "mostrecent",
  "reviewId": "14661870031",
  "rating": 4,
  "title": "Really duo is this the best you could do",
  "text": "Duolingo is the best place to learn a new language but this last challenge was so hard to complete...",
  "version": "7.144.0",
  "author": "Simply apps",
  "authorUrl": "https://itunes.apple.com/us/reviews/id347567423",
  "voteCount": 0,
  "voteSum": 0,
  "date": "2026-10-13T07:15:04-07:00",
  "scrapedAt": "2026-10-15T00:47:18+00:00"
}
```

| Field | Meaning |
|---|---|
| `reviewId` | Apple's ID for the review. Stable, so you can de-duplicate across runs. |
| `rating` | Stars, 1 to 5. |
| `title`, `text` | The review as written. |
| `version` | App version the reviewer was using. Group by this to compare releases. |
| `date` | When the review was posted or last edited, with time zone. |
| `voteCount`, `voteSum` | How many people voted on the review's helpfulness, and how many found it helpful. |
| `author`, `authorUrl` | The public nickname and review link Apple shows. Nothing else about reviewers is collected. |
| `country`, `sort` | Which storefront and sort order the review came from. |
| `appName` … `currentVersion` | App details from Apple's Lookup API (when `includeAppDetails` is on). |

### Export to CSV or Excel

After a run, open the **Storage** tab and download the dataset as CSV, Excel, JSON, XML or HTML. From the API, add `?format=csv` (or `xlsx`, `json`) to the dataset items URL. You can also send results straight to Google Sheets, Slack, Airtable or a webhook with Apify integrations.

### Use it as an App Store reviews API

**Python**

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("steady-data/app-store-reviews-scraper").call(run_input={
    "apps": ["389801252"], "countries": ["us"], "maxRating": 2,
})
for review in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(review["rating"], review["version"], review["title"])
```

**JavaScript**

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

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('steady-data/app-store-reviews-scraper').call({ apps: ['duolingo'], since: '2026-10-01' });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'reviews');
```

**cURL** (runs the actor and returns the reviews in one call)

```bash
curl -X POST "https://api.apify.com/v2/acts/steady-data~app-store-reviews-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>&format=csv" \
  -H "Content-Type: application/json" \
  -d '{"apps": ["389801252"], "maxReviewsPerApp": 200}'
```

**No code:** in n8n, Make or Zapier, use the Apify app's "Run Actor" step with `steady-data/app-store-reviews-scraper` and the same JSON input. Add a schedule in Apify (for example daily, with `since` set to yesterday) to monitor new reviews.

### Use it from AI agents (MCP)

Apify's hosted MCP server lets Claude, ChatGPT, Cursor and other MCP clients call this actor as a tool. Limit the server to this actor with the `tools` parameter:

```
https://mcp.apify.com?tools=steady-data/app-store-reviews-scraper
```

**Claude Code**

```bash
claude mcp add --transport http app-store-reviews "https://mcp.apify.com?tools=steady-data/app-store-reviews-scraper"
```

**Any client that takes an `mcpServers` config** (sign in with Apify on first use, or add an `Authorization: Bearer <APIFY_TOKEN>` header):

```json
{
  "mcpServers": {
    "app-store-reviews": { "url": "https://mcp.apify.com?tools=steady-data/app-store-reviews-scraper" }
  }
}
```

Then ask in plain language, for example: "Get the latest one- and two-star US reviews for Duolingo and group the complaints by theme."

### Pricing

**$0.0001 per review ($0.10 per 1,000)**, charged only for reviews saved to your dataset. Apify adds a small per-run start fee.

| Job | Reviews | Cost |
|---|---|---|
| One app, latest reviews, one country | 500 | about $0.05 |
| 10 competitor apps, US | 5,000 | about $0.50 |
| One app, 20 countries | 10,000 | about $1.00 |

Apps with no reviews cost nothing beyond the start fee. Reviews removed by your star filter aren't charged. If you set a maximum cost for the run, it stops cleanly at that amount and keeps everything already saved.

### Limits

- **500 reviews per app, per country, per sort order.** Apple's public feed serves 10 pages of 50 and no more. For more history, add countries or run both sort orders (they overlap partly).
- **Apple's feed is sometimes patchy.** It occasionally serves an empty page in the middle of an app's reviews. The actor retries those pages and keeps going instead of stopping. If pages stay empty, the run's status message says so, and a re-run later usually fills the gap.
- The feed usually trails the App Store by a day or two.
- Only written reviews appear. Star-only ratings are counted in `ratingCount` but have no text.
- Developer replies to reviews aren't in Apple's public feed, so they aren't in the output.
- Mac App Store apps aren't covered.

### App Store vs Google Play

This actor covers Apple's App Store only. Google Play reviews come from a different source with different rules, so they aren't included. If you need both, run a Google Play reviews actor alongside this one and join the datasets on app name.

### FAQ

**Do I need an Apple developer account or App Store Connect?**
No. It uses Apple's public feed, so it works for any app, including competitors'.

**How do I get only new reviews each day?**
Schedule a daily run with `sort: "mostrecent"` and `since` set to yesterday's date, or de-duplicate on `reviewId`.

**Why did I get fewer than 500 reviews?**
The app may have fewer written reviews in that country, your `since` or star filter may have cut the list, or Apple's feed served empty pages. The status message says so when that happens, and those runs are not charged for the missing reviews.

**Which countries are supported?**
Every App Store storefront that has the public reviews feed, about 155. Use two-letter codes, or `all`.

**Can I use the data for sentiment analysis or LLM summaries?**
Yes. Each row has the rating, text and version, which is what most sentiment and topic workflows need.

**Is it legal?**
It collects only what Apple publishes in its public reviews feed, with no login. You're responsible for how you use the data, including privacy laws where you operate.

### Problems or requests

Open an issue on the **Issues** tab with the run link. Failed runs are checked within a day.

# Actor input Schema

## `apps` (type: `array`):

App Store URLs, numeric app ids, or app names (a name is matched to the top App Store search result).

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

Two-letter App Store country codes, e.g. us, gb, de. Reviews are separate per country. Use "all" to go through every storefront.

## `sort` (type: `string`):

Apple lets you read the newest reviews or the most helpful ones.

## `maxReviewsPerApp` (type: `integer`):

Stop after this many reviews for each app, across all countries. Apple shows at most 500 per country per sort order.

## `since` (type: `string`):

Only with "Most recent". Stop at reviews older than this date (YYYY-MM-DD).

## `minRating` (type: `integer`):

Only keep reviews with at least this many stars (1-5). Skipped reviews are not charged.

## `maxRating` (type: `integer`):

Only keep reviews with at most this many stars (1-5), e.g. 2 for complaints only. Skipped reviews are not charged.

## `includeAppDetails` (type: `boolean`):

Adds app name, developer, genre, average rating, rating count and current version to every row. Free.

## Actor input object example

```json
{
  "apps": [
    "https://apps.apple.com/us/app/duolingo-language-lessons/id570060128"
  ],
  "countries": [
    "us"
  ],
  "sort": "mostrecent",
  "maxReviewsPerApp": 500,
  "includeAppDetails": true
}
```

# Actor output Schema

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

All reviews, in the Reviews table view.

## `reviewsAllFields` (type: `string`):

All reviews with every field, including app details.

# 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 = {
    "apps": [
        "https://apps.apple.com/us/app/duolingo-language-lessons/id570060128"
    ],
    "countries": [
        "us"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("steady-data/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 = {
    "apps": ["https://apps.apple.com/us/app/duolingo-language-lessons/id570060128"],
    "countries": ["us"],
}

# Run the Actor and wait for it to finish
run = client.actor("steady-data/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 '{
  "apps": [
    "https://apps.apple.com/us/app/duolingo-language-lessons/id570060128"
  ],
  "countries": [
    "us"
  ]
}' |
apify call steady-data/app-store-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,steady-data/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/f1z3S0sQwG7WIW5p5/builds/UKXO7vACWk9RuGfJ9/openapi.json