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 · Input · More than 500 · Examples · Output fields · Export · API · AI agents (MCP) · Pricing · Limits · 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.

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

Input examples

Latest reviews for one app

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

Complaints only since a date, US and UK

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

Competitor sweep across three apps

{
  "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

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

Output fields

One dataset item per review:

{
  "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

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

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)

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

$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):

{
  "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.