App Store Reviews (via Apify)
io.github.retracnv1.0.0更新於 Oct 3, 2026
App Store reviews for AI agents: any app or country, past the 500-review limit, with dev replies.
概覽
讓助理取得任一應用程式與地區的 Apple App Store 評論,包含開發者回覆,並突破 Apple 500 則評論來源的限制。
- 功能
- 這個遠端 MCP 伺服器封裝了一個 Apify Actor,用來擷取 Apple App Store 評論。每則評論會回傳星等、標題、內容、日期、評論者公開名稱、是否經過編輯,以及開發者回覆與其日期,另外還有應用程式名稱、開發者、整體評分和 App Store 連結。它接受 App Store 連結、數字 App ID 或應用程式名稱,支援一次執行多個國家、依最新或最有幫助排序以及星等篩選,並可啟用僅擷取新評論模式用於排程監控。
- 適用情境
- 當助理需要一個或多個應用程式或商店地區的 App Store 評論資料(包括競品應用程式)時使用,或當你需要超過 Apple 公開來源每國最新 500 則評論時使用。它也適合定期監控新評論。
- 執行需求
- 遠端 MCP 端點 mcp.apify.com,需要在 Authorization 標頭中以 'Bearer ' 形式提供 Apify API 權杖。免費 Apify 帳號即可取得該權杖。依評論數量計費,因此需要 Apify 方案或額度。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 App Store Reviews (via Apify),將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"app-store-reviews": {
"type": "http",
"url": "https://mcp.apify.com/?tools=automationnation/app-store-reviews-scraper"
}
}
}README
App Store Reviews Scraper & API: past the 500-review limit, with developer replies
App Store Reviews Scraper is an Apify Actor that extracts Apple App Store reviews for any app and country — star rating, title, text, date, author and the developer's reply — and goes past the 500-review limit of Apple's public review feed, at $0.08 per 1,000 reviews. It works as an App Store reviews API: call it from code, schedule it to monitor new reviews, or let AI agents use it through Apify's MCP server.
Price: $0.08 per 1,000 reviews ($0.05–$0.07 on paid plans) · Run it: https://apify.com/automationnation/app-store-reviews-scraper · Guide: https://retracn.github.io/automationnation-actors/app-store-reviews-scraper/
Quick facts
- One row per review: stars, title, text, date, the reviewer's public name, whether the review was edited, and the developer's reply with its date, plus app name, developer, overall rating and App Store URL.
- Past 500 reviews: most App Store scrapers read Apple's public RSS feed, which stops at the newest 500 reviews per country. This Actor reads the review API behind apps.apple.com and pages back tens of thousands of reviews for popular apps.
- Any app and storefront: App Store URLs, numeric App IDs or app names, several countries per run; newest or most helpful first; star filters.
- Only new reviews mode for scheduled monitoring; repeats aren't charged. In a test run, 5,000 reviews from 3 apps in 2 countries took under 2 minutes.
- Price: $0.08 per 1,000 reviews on the Free plan ($0.05–$0.07 on paid plans), with no caps on free-plan runs or reviews. Apify's free $5 monthly credit covers over 60,000 reviews.
Example input
Run it from code
REST API
Python — see examples/python_example.py
JavaScript — see examples/node_example.mjs
Use it with AI agents (MCP)
Hosted MCP server URL (Claude, ChatGPT, Cursor and other clients with remote MCP support):
Local config for Claude Desktop / Cursor — mcp/claude_desktop_config.json:
FAQ
Why do most App Store scrapers stop at 500 reviews? Apple's public RSS review feed only returns the newest 500 reviews per country (10 pages of 50). App Store Reviews Scraper reads the review API that apps.apple.com itself uses, which pages much further back, and keeps the feed as a fallback.
Does it include developer responses? Yes. Every review the developer answered has replyText and replyDate.
Is there an official App Store reviews API? Apple's App Store Connect API returns reviews only for apps in your own developer account. To read reviews of any app, including competitors', App Store Reviews Scraper returns the public reviews shown on the App Store through Apify's REST API, clients, integrations and MCP.
How much does it cost? $0.08 per 1,000 reviews on Apify's Free plan and $0.05–$0.07 on paid plans. Apps that can't be found and repeats in Only new reviews mode are free.
Can I get reviews from several countries? Yes. List the storefronts in countries; each app is read once per country and every row has its country.
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This repository holds usage examples. The scraper itself runs on the Apify platform; you need a free Apify account and API token. Examples are MIT licensed.
來源:README.md,提交 109f987
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0版本歷史
1- v1.0.0最新Oct 3, 2026


