# AI App Store Reviews Scraper (`agentdataco/ai-app-reviews`) Actor

Get the latest App Store reviews for AI apps (ChatGPT, Claude, Gemini, Grok, Perplexity, Copilot or any app) by country, with star filters. Uses Apple's public reviews feed.

- **URL**: https://apify.com/agentdataco/ai-app-reviews.md
- **Developed by:** [Agent Data Co](https://apify.com/agentdataco) (community)
- **Categories:** AI, Social media
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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

## AI App Store Reviews Scraper — ChatGPT, Claude, Gemini, Grok

Get the latest App Store reviews for AI apps (ChatGPT, Claude, Gemini, Grok, Perplexity, Copilot or any app) by country, with star filters. Uses Apple's public reviews feed.

### What does AI App Store Reviews do?

Looks up each app on the App Store, then reads Apple's public customer-reviews RSS feed (most recent first, up to 500 reviews per app per country). Returns stars, title, text, app version and date. Reviewer nicknames are excluded by default.

### Why use it?

- Apple's public RSS feed — no login, no anti-bot evasion
- Multi-country, multi-app in one run
- Star filters for complaint mining (1–2★) or praise (5★)
- Fail-loudly empty-result guard

### Data source

Apple iTunes Search API and the public App Store customer-reviews RSS feed (itunes.apple.com/{country}/rss/customerreviews).

### Input

- **apps**: App names to look up
- **appIds**: Numeric App Store IDs
- **countries**: Country codes
- **maxPagesPerApp**: 1–10 pages of 50
- **minRating / maxRating**: Star filter
- **includeReviewerName**: Off by default

Example input:

```json
{
  "apps": [
    "ChatGPT",
    "Claude by Anthropic"
  ],
  "countries": [
    "us",
    "gb"
  ],
  "maxPagesPerApp": 2,
  "maxRating": 2
}
```

### Output

Each dataset item looks like this:

```json
{
  "appId": "6448311069",
  "appName": "ChatGPT",
  "country": "gb",
  "rating": 5,
  "title": "Great",
  "text": "I love working with ChatGPT",
  "appVersion": "1.2026.272",
  "updatedAt": "2026-10-12T22:15:58-07:00"
}
```

Export as JSON, CSV, Excel or HTML, or pull via the Apify API, webhooks, Make, Zapier, n8n or the Apify MCP server.

### How much does it cost?

Pay per event: **$0.001 per run** + **$0.0003 per result** (≈ $0.30 per 1,000 results). You are never charged for results on a failed run: if no data is found, the run fails loudly with an explanation instead of returning an empty "success".

### Use cases

- AI product teams tracking user sentiment vs competitors
- Complaint mining for feature ideas
- Market research on AI assistants by country
- Feeding reviews to an LLM for weekly summaries

### Scheduling & monitoring

Schedule it daily or weekly in Apify Console and connect a webhook/Slack/email integration to get new items automatically.

### FAQ

**Is this legal?** It uses Apple's public RSS feeds and Search API. Reviewer nicknames are excluded by default. No personal data is collected.

**Something broke?** Open an issue on the Issues tab; the actor is tested daily.

***

Built and maintained by **Agent Data Co** — reliable AI-ecosystem data for agents and analysts.

### More AI-ecosystem data from Agent Data Co

This Actor is part of [Agent Data Co](https://agentdataco.com): daily, archived data on AI agents, MCP servers, LLM pricing, AI pricing pages, Hugging Face and Show HN launches, with **history and trends** via a REST API and an MCP server (`https://agentdataco.com/mcp`). Free sample: https://agentdataco.com/api/v1/sample · Plans from $19/mo: https://agentdataco.com/#pricing

# Actor input Schema

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

App Store search terms; the top match per country is used.

## `appIds` (type: `array`):

Optional numeric App Store IDs (e.g. 6448311069 for ChatGPT).

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

2-letter App Store country codes.

## `maxPagesPerApp` (type: `integer`):

50 reviews per page, max 10 (Apple feed limit).

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

Filter by star rating.

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

Filter by star rating (e.g. 1–2 for complaints).

## `includeReviewerName` (type: `boolean`):

Off by default (data minimisation).

## `maxItems` (type: `integer`):

Cap on results.

## `allowEmpty` (type: `boolean`):

Do not fail on zero results.

## Actor input object example

```json
{
  "apps": [
    "ChatGPT",
    "Claude by Anthropic",
    "Google Gemini",
    "Grok - AI Assistant",
    "Perplexity - Ask Anything",
    "Microsoft Copilot"
  ],
  "appIds": [],
  "countries": [
    "us"
  ],
  "maxPagesPerApp": 2,
  "minRating": 1,
  "maxRating": 5,
  "includeReviewerName": false,
  "maxItems": 200,
  "allowEmpty": false
}
```

# Actor output Schema

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

Dataset items produced by this run (one item per charged result).

## `runSummary` (type: `string`):

Count of results, duration and whether the charge limit was hit.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentdataco/ai-app-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("agentdataco/ai-app-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 '{}' |
apify call agentdataco/ai-app-reviews --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentdataco/ai-app-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/G9We2VFfVJRraYoxf/builds/igqC4uMPSNVZXJQ3n/openapi.json