App Store Reviews API — Public Reviews as JSON | FetchLayer
Unofficial Third-party API
2 endpoints live

App Store reviews,
ready for your code and AI.

Ratings & reviews Country filter AI-ready JSON

Fetch public App Store reviews for any app as structured JSON. Filter by country, language, and platform, then send ratings and review text to your product, research, monitoring, or AI workflow.

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POST /appstore/reviews
200 OK

Request

$ curl -X POST https://api.fetchlayer.dev/appstore/reviews \
  -H "Authorization: Bearer ss-your-key" \
  -H "Content-Type: application/json" \
  -d '{"appId":"1232780281","country":"us","pages":1}'

Response

{
  "reviews": [{
    "rating": 1,
    "title": "Latest update crashes",
    "body": "It closes whenever I open...",
    "version": "4.2.0",
    "date": "2026-07-28T12:00:00Z"
  }],
  "pagesFetched": 1
}

Used by developers at

Individual developers or teams — not official partnerships

Built for feedback workflows

Fetch the public signal. Use it wherever your team works.

Public app reviews

Retrieve publicly visible reviews for an App Store app by its numeric app ID—without App Store Connect credentials.

Regional feedback

Narrow review retrieval by country, language, and Apple platform when you need market-specific feedback.

Recent or helpful

Choose recent feedback to monitor what changed, or helpful reviews to surface the most visible customer signal.

Run on your schedule

Call the API from a cron job or automation to keep a feed of new feedback in your own database or alerting workflow.

AI-ready JSON

Pass structured review text, ratings, versions, and dates to an LLM to group bugs, feature requests, and recurring complaints.

Find the app first

Use the App Store search endpoint to resolve an app by name or keyword before fetching its reviews.

FetchLayer Research Chat

Analyze App Store reviews with AI—then export the results to CSV.

Prefer not to write code? Give FetchLayer Research Chat an app, ask what customers love or dislike, and turn the review set into a structured file you can use in a spreadsheet, report, or product workflow.

  • Ask questions in plain English
  • Analyze themes, sentiment, and pain points
  • Download the structured results as CSV or JSON
Analyze reviews in Chat

No code or setup required · Uses your FetchLayer credits

App Store research

Analyze the recent App Store reviews for this app. Group recurring bugs, feature requests, and praise by theme, then export the reviews and classifications as CSV.

Y

I grouped the reviews into six themes and highlighted the issues most closely tied to the latest app version. The full review-level analysis is ready to download.

app-store-review-analysis.csv

126 reviews · 8 columns · ready to download

CSV

From raw feedback to action

One request is the start of the workflow.

Store the structured response, run it on a schedule, pass it to an LLM, or feed it into the system your team already uses. FetchLayer handles retrieval so you can focus on the outcome.

  1. 01

    Resolve an app

    Search the App Store by name or use the numeric app ID from its public listing.

  2. 02

    Fetch the review pages you need

    Select country, language, platform, sorting, and pagination controls for the feedback you want.

  3. 03

    Turn feedback into action

    Store the JSON, trigger an alert, compare competitors, or ask an AI agent to summarize the recurring themes.

MCP & agents

Live

Your AI already knows how to use this.

Use the App Store endpoint directly from your MCP-compatible agent. Ask it to retrieve public feedback, identify patterns, and turn the result into a useful brief without writing integration glue.

1
Pick your editor
2
Agent discovers 2 tools
3
Query any platform instantly
connect your agent ~30s

Pick your editor and we hand you the config with your key already in it — no JSON to hand-edit, no wrapper code.

Get your free API key

Free tier · no credit card · any MCP host

New chat fetchlayer connected

Fetch recent one-star App Store reviews for a competitor and summarize the three most repeated complaints, including the app version each complaint appears in.

Used fetchlayer.appstore_reviews

Fetched the public review pages and grouped the feedback. The leading issues are crashes after the latest update, slow syncing, and requests for offline access.

Ask a follow-up…

Works with every MCP-compatible tool

Cursor
Claude
VS Code
Windsurf
Cline
Hermes
OpenClaw
Kiro
No wrapper code
All 2 endpoints exposed as tools
Official & maintained
Free to install

Use cases

What developers build with App Store review data.

Same API, endless applications. Here is what teams ship with public review data.

01

Competitor intelligence

Compare public reviews across competing apps to find recurring complaints, unmet requests, and product gaps.

competitorsreviewsresearch
02

AI agent context

Give Claude, Codex, or your MCP agent structured reviews with app versions and ratings attached.

llmagentsmcp
03

Review monitoring

Poll recent reviews on a schedule and alert the right team when a complaint cluster begins to grow.

alertsmonitoringcron
04

Release intelligence

Track reviews by app version to catch regressions and understand what changed after a rollout.

releasesbugsversions
05

Product feedback

Turn recurring bugs, requests, and praise into a clean product-research dataset or CSV export.

feedbackcsvroadmap
06

Market research

Compare public feedback by country and language to understand how customer needs differ across markets.

marketslocalesinsight

Compare approaches

Spend time on the insight, not the collection layer.

What you needFetchLayerOfficial APIBuild it yourself
Public competitor review accessOwner apps onlyYou build it
Bearer auth from one accountApple setupYou manage it
Structured JSONYou parse it
Ready for AI and MCP workflowsYour integrationYour integration

FetchLayer provides access to publicly available data. It is not affiliated with, endorsed by, or sponsored by the platform.

Pricing

Start free. Scale when ready.

Pay per request with no commitment, or lock in a flat monthly rate with built-in savings.

Free plan — 30 requests

Verify responses, inspect the API, no credit card required.

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$1.99

per 1,000 requests

$0.00199 per request · credits never expire

How credits work — no multipliers

One credit = one API call, on every endpoint and platform. No matter how many results come back, you pay for the call, not the output size. Most scraping APIs charge multipliers of 5x, 25x, even 75x per call depending on the target — here it's always 1.

  • No multipliers — 1 request = 1 credit
  • No monthly commitment
  • Credits never expire
  • Same API & MCP access as subscribers
  • ∞ req/min, ∞ API keys
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Credits stay until you use them. No monthly reset, no pressure to hit a quota.

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Commitments

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Access

Every endpoint and MCP included. Not a limited tier — same data as any subscriber.

API reference

Every parameter, documented.

All requests are POST with a JSON body and Bearer auth header.

POST /appstore/search

Search the App Store for apps by name or keyword. Returns matching apps with ratings, subtitle, and screenshots.

query* string Search query (app name or keyword)
country string Two-letter country code, e.g. 'us', 'gb', 'jp'. Defaults to us.
platform string 'iphone' | 'ipad' | 'mac' | 'appletv' | 'watch' | 'realityDevice'
geo string Two-letter geo code for regional results
POST /appstore/reviews

Fetch customer reviews for an app by its App Store ID. Supports filtering by platform, country, language, and pagination.

appId* string App Store app ID (numeric)
country string Two-letter country code, e.g. 'us', 'gb', 'jp'. Defaults to us.
platforms string[] One or more of 'iphone' | 'ipad' | 'mac' | 'appletv' | 'watch' | 'realityDevice'
lang string Language code, e.g. 'en', 'ja'
geo string Two-letter geo code for regional results
pages number Number of pages to fetch. Billed per page actually retrieved. Default 1.
reviewsPerPage number Reviews per page (max 20). Default 20.
sort string 'recent' or 'helpful'. Default recent.
since string ISO 8601 date (e.g. 2026-01-31). Only returns reviews on or after this date. With sort=recent, pagination also stops once it passes the cutoff — a narrow window can cost far fewer credits than the requested page count.

Fields marked * are required. Full API reference →

FAQ

Common questions.

Can I fetch reviews for an app I do not own?

Yes. FetchLayer retrieves publicly available App Store reviews by app ID. You use your FetchLayer API key, not the app owner’s App Store Connect credentials.

What fields are included in an App Store review?

Reviews include the rating, title, body text, author display name, app version, date, helpful count, and a unique review ID where available.

Can I filter reviews by country or language?

Yes. The reviews endpoint supports country, language, platform, sorting, date, and pagination controls so you can retrieve the feedback relevant to your workflow.

Can I fetch only reviews since a certain date?

Yes. Pass a since date (ISO 8601, e.g. 2026-01-31) and only reviews on or after that date are returned. With the default sort=recent, the scraper also stops paginating as soon as it passes the cutoff — so a narrow date window is billed for far fewer pages than the pages parameter alone would suggest. With sort=helpful, Apple's feed isn't date-ordered, so since still filters the results but every requested page is fetched.

Can I use the data with an AI model?

Yes. The API returns structured JSON that you can store, send to an LLM, or access through FetchLayer’s MCP server to find recurring complaints, feature requests, and product feedback.

Can I analyze and export App Store reviews without code?

Yes. FetchLayer Research Chat can retrieve public App Store reviews, analyze recurring themes with AI, and export the structured results as a downloadable CSV or JSON file.

How does billing work?

Review retrieval is billed per page actually fetched. Request the amount of data you need and inspect pagesFetched in the response for the amount retrieved.

Start pulling App Store reviews today.

Get a free API key, make your first request, and put public feedback to work in your own product or research workflow.