# App Store & Google Play Scraper 📱 (ratings, reviews monitor) (`tagadanar/app-intel-scraper`) Actor
Scrape apps from the Apple App Store and Google Play: ratings, rating counts, installs, pricing, categories, versions and descriptions. Search or fetch by id. Turn on the monitor for new-review alerts to Slack. Keyless, no browser. $2.50 per 1,000 apps.
- **URL**: https://apify.com/tagadanar/app-intel-scraper.md
- **Developed by:** [Tagada Data](https://apify.com/tagadanar) (community)
- **Categories:** Developer tools, SEO tools, Automation
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.75 / 1,000 app scrapeds
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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
## App Store & Google Play Scraper: Ratings, Reviews, Installs & Pricing
Pull structured app intelligence from the Apple App Store and Google Play in one run. Give it a search term, an Apple trackId or a Google package name and you get back a clean, unified record per app: name, developer, rating and rating count, installs, price, category, version, description, screenshots and update date. Turn on the review monitor and it remembers which reviews it has already reported, so scheduled runs surface only new reviews and can post them straight to Slack.
Apple is the fast, reliable spine here. It reads Apple's own keyless iTunes JSON API, so those records are complete and the runs are quick. There is no browser to time out, no login, and no residential proxy requirement: both stores answer plain datacenter requests, so you are not paying a proxy surcharge on top of every app.
### What you get per app
| Field | Description |
| --- | --- |
| `store`, `appId` | `apple` or `google`, and the Apple trackId or Google package name |
| `name`, `developer`, `url` | App title, publisher and the canonical store listing URL |
| `price` | `{ amount, currency, formatted }`, `Free` when the app costs nothing |
| `rating`, `ratingCount` | Average star rating (0 to 5) and how many ratings it has |
| `installs` | Google Play install band, e.g. `10,000,000,000+` (Apple does not expose this, so it is `null`) |
| `category` | Primary store category |
| `version`, `releaseNotes` | Current version and its what's-new text |
| `description` | Full listing text, HTML stripped |
| `contentRating` | Age / content rating, e.g. `4+` or `Everyone` |
| `screenshots`, `icon` | Up to 8 screenshot URLs and the app icon |
| `releasedAt`, `updatedAt` | First release and last update dates where the store exposes them |
### Who uses it
- **ASO and app marketers** tracking their own and competitors' ratings, versions and store copy over time.
- **Competitive and market intelligence**: pull a whole category of apps for one term and compare ratings, install bands and pricing.
- **Product and support teams** watching for new one- and two-star reviews the moment they land.
- **Investors and analysts** sizing traction from install bands, rating counts and update cadence.
- **Agents and data pipelines** that need app data as clean JSON, over MCP or a scheduled run.
### Input examples
Look up one app on both stores by name:
```json
{
"store": "both",
"terms": ["notion"],
"maxResults": 10,
"country": "us"
}
````
Fetch specific apps directly by id:
```json
{
"store": "apple",
"appIds": ["1232780281", "310633997"],
"country": "us"
}
```
A new-review alert feed for your app (schedule this and point it at Slack):
```json
{
"store": "apple",
"appIds": ["1232780281"],
"reviewMonitor": true,
"maxReviewsPerApp": 200,
"webhookUrl": "https://hooks.slack.com/services/XXX/YYY/ZZZ"
}
```
### Output samples
An app record:
```json
{
"store": "apple",
"appId": "1232780281",
"name": "Notion: Notes, Tasks, AI",
"developer": "Notion Labs, Incorporated",
"url": "https://apps.apple.com/us/app/notion-notes-tasks-ai/id1232780281",
"price": { "amount": 0, "currency": "USD", "formatted": "Free" },
"rating": 4.78,
"ratingCount": 87829,
"installs": null,
"category": "Productivity",
"version": "1.7.317",
"contentRating": "4+",
"updatedAt": "2026-07-07T18:43:58Z",
"source": "apps.apple.com"
}
```
A review record (monitor mode):
```json
{
"store": "apple",
"appId": "1232780281",
"appName": "Notion: Notes, Tasks, AI",
"reviewId": "14267353065",
"rating": 3,
"title": "AI chatbot feature is very buggy",
"body": "Love the app overall but the new assistant keeps losing context...",
"author": "Jakobihaskell",
"appVersion": "1.7.316",
"source": "apps.apple.com"
}
```
| Review field | Description |
| --- | --- |
| `reviewId` | Stable id used to dedupe across scheduled runs |
| `rating`, `title`, `body` | Star rating, headline and full review text (Google Play reviews have no title, so it is null there) |
| `author`, `appVersion` | Reviewer name and the app version they reviewed |
| `reviewedAt` | When the review was posted (Google Play rows) |
### Pricing
You pay per app returned and per new review in monitor mode. Platform usage (compute and any proxy) is billed to your run at Apify cost, so there is no subscription.
| Event | Price |
| --- | --- |
| Actor start | $0.00005 (≈ zero) |
| App scraped | $0.0025 per app ($2.50 per 1,000) |
| Review scraped (monitor mode) | $0.0005 per review ($0.50 per 1,000) |
| Digest sent (monitor mode) | $0.03 per digest |
### FAQ
**Which stores does it cover?** Both the Apple App Store and Google Play. Set `store` to `apple`, `google` or `both`.
**Is Google Play as reliable as Apple?** No, and this actor is honest about it. Apple exposes a clean public JSON API, so those records are complete and stable. Google Play has no public API, so app data is parsed from the page's server-rendered HTML. That parsing is best-effort: it reads name, developer, rating, rating count, installs, price, category, description, content rating, icon, screenshots and the last-updated date reliably today, but Google can change the page layout at any time. When a field moves, the actor returns `null` for it instead of failing the run. Note that Google no longer prints an app `version` on the public page, so that field is usually `null` on Google Play.
**What review coverage do I get?** Both stores. Apple reviews come from the most-recent reviews feed (up to about 500 per app). Google Play reviews come from the store's own reviews endpoint, paged newest-first until you have as many as you asked for. Note that Google Play reviews carry no title, so the `title` field is null on Google rows.
**How do I only get new reviews?** Turn on `reviewMonitor` and schedule the actor. It remembers reviews from previous runs (per `monitorName`) and returns only new ones, and it can post them to a webhook or Slack.
**Does it need a proxy?** Not for light use. Both stores answer plain requests. If you run at high volume and start seeing blocks, enable an Apify proxy in the input.
**Can I use it from an AI agent?** Yes. It returns plain JSON and runs headless, so it plugs into agent tools, MCP servers and data pipelines without a browser.
***
### Something missing?
If you need an extra field, another source, or Google Play reviews, open an issue on this Actor and describe it. I read every request and small additions usually ship within days. More monitors and data Actors are on [my profile](https://apify.com/tagadanar).
*App Store scraper, Google Play scraper, app ratings API, app reviews monitor, ASO data, app store intelligence, scrape App Store, scrape Google Play, app install counts, competitor app tracking, new review alerts.*
# Actor input Schema
## `store` (type: `string`):
Which store to scrape. Apple is the fast, reliable path (clean JSON API). Google Play is parsed from page HTML and is best-effort.
## `terms` (type: `array`):
One search per entry, e.g. notion, habit tracker, budget app. Leave empty if you pass app ids or package names directly.
## `appIds` (type: `array`):
Optional. Numeric Apple trackIds to fetch directly, e.g. 1232780281 (Notion), 310633997 (WhatsApp). Used when store includes Apple.
## `packageNames` (type: `array`):
Optional. Google Play package names to fetch directly, e.g. com.whatsapp, notion.id. Used when store includes Google.
## `country` (type: `string`):
Two-letter storefront code, e.g. us, gb, fr, in. Affects search results, pricing and reviews.
## `maxResults` (type: `integer`):
Total app records to return across all terms and ids.
## `reviewMonitor` (type: `boolean`):
For each resolved app, fetch recent reviews and return only ones not seen on previous runs. Covers both the Apple App Store and Google Play. Combine with a schedule and a webhook for a new-review alert feed.
## `maxReviewsPerApp` (type: `integer`):
In review-monitor mode, how many most-recent reviews to pull per app before deduping. Apple caps the feed at about 500.
## `monitorName` (type: `string`):
Label for the remembered-reviews set. Use different names to track different app lists independently.
## `webhookUrl` (type: `string`):
Optional. In review-monitor mode, new reviews are posted here as a digest (Slack incoming webhook or any endpoint accepting JSON).
## `proxyConfiguration` (type: `object`):
Optional. Enable a proxy if you run at high volume and start seeing blocks. Not needed for light use: both stores answer plain datacenter requests.
## Actor input object example
```json
{
"store": "apple",
"terms": [
"notion"
],
"country": "us",
"maxResults": 10,
"reviewMonitor": false,
"maxReviewsPerApp": 100,
"monitorName": "default",
"proxyConfiguration": {
"useApifyProxy": false
}
}
```
# Actor output Schema
## `apps` (type: `string`):
One item per app record, plus one item per new review in monitor mode, in the default 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"terms": [
"notion"
],
"maxResults": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("tagadanar/app-intel-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"terms": ["notion"],
"maxResults": 10,
}
# Run the Actor and wait for it to finish
run = client.actor("tagadanar/app-intel-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"terms": [
"notion"
],
"maxResults": 10
}' |
apify call tagadanar/app-intel-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=tagadanar/app-intel-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "App Store & Google Play Scraper 📱 (ratings, reviews monitor)",
"description": "Scrape apps from the Apple App Store and Google Play: ratings, rating counts, installs, pricing, categories, versions and descriptions. Search or fetch by id. Turn on the monitor for new-review alerts to Slack. Keyless, no browser. $2.50 per 1,000 apps.",
"version": "0.1",
"x-build-id": "UiHnydvcMI1konlwt"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/tagadanar~app-intel-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-tagadanar-app-intel-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/tagadanar~app-intel-scraper/runs": {
"post": {
"operationId": "runs-sync-tagadanar-app-intel-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/tagadanar~app-intel-scraper/run-sync": {
"post": {
"operationId": "run-sync-tagadanar-app-intel-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"store": {
"title": "Store",
"enum": [
"apple",
"google",
"both"
],
"type": "string",
"description": "Which store to scrape. Apple is the fast, reliable path (clean JSON API). Google Play is parsed from page HTML and is best-effort.",
"default": "apple"
},
"terms": {
"title": "Search terms",
"type": "array",
"description": "One search per entry, e.g. notion, habit tracker, budget app. Leave empty if you pass app ids or package names directly.",
"items": {
"type": "string"
}
},
"appIds": {
"title": "Apple app ids (trackId)",
"type": "array",
"description": "Optional. Numeric Apple trackIds to fetch directly, e.g. 1232780281 (Notion), 310633997 (WhatsApp). Used when store includes Apple.",
"items": {
"type": "string"
}
},
"packageNames": {
"title": "Google package names",
"type": "array",
"description": "Optional. Google Play package names to fetch directly, e.g. com.whatsapp, notion.id. Used when store includes Google.",
"items": {
"type": "string"
}
},
"country": {
"title": "Country / storefront",
"type": "string",
"description": "Two-letter storefront code, e.g. us, gb, fr, in. Affects search results, pricing and reviews.",
"default": "us"
},
"maxResults": {
"title": "Max apps",
"minimum": 1,
"maximum": 500,
"type": "integer",
"description": "Total app records to return across all terms and ids.",
"default": 20
},
"reviewMonitor": {
"title": "Review monitor (new reviews only)",
"type": "boolean",
"description": "For each resolved app, fetch recent reviews and return only ones not seen on previous runs. Covers both the Apple App Store and Google Play. Combine with a schedule and a webhook for a new-review alert feed.",
"default": false
},
"maxReviewsPerApp": {
"title": "Max reviews per app",
"minimum": 1,
"maximum": 500,
"type": "integer",
"description": "In review-monitor mode, how many most-recent reviews to pull per app before deduping. Apple caps the feed at about 500.",
"default": 100
},
"monitorName": {
"title": "Monitor name",
"type": "string",
"description": "Label for the remembered-reviews set. Use different names to track different app lists independently.",
"default": "default"
},
"webhookUrl": {
"title": "Webhook / Slack URL",
"type": "string",
"description": "Optional. In review-monitor mode, new reviews are posted here as a digest (Slack incoming webhook or any endpoint accepting JSON)."
},
"proxyConfiguration": {
"title": "Proxy",
"type": "object",
"description": "Optional. Enable a proxy if you run at high volume and start seeing blocks. Not needed for light use: both stores answer plain datacenter requests.",
"default": {
"useApifyProxy": false
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```