app-reviews

把 App Store 评价变成产品研究证据，发现痛点、机会和版本风险 | Turn App Store reviews into product research evidence: pain points, opportunities, and version risks.

ZReviewTender fetches app reviews from the App Store and Google Play Console using the new Stability API, and resends them to Slack or integrates with your workflow.

Heimdall — MCP server for the Apple App Store Connect API and App Store Server API (StoreKit 2). 890 tools across 13 profiles, generated from Apple's OpenAPI spec, plus one-call macros for worldwide pricing, submission readiness and metadata diffs, and confirm-before-write safety. Works with Claude, Codex, Cursor and any MCP client.

Google Play scraper for Node.js with a fully typed TypeScript API. App details, search, top charts, reviews, permissions and data safety. A modern replacement for the unmaintained google-play-scraper.

Node.js library written in TypeScript for sending App Store app reviews to Slack.

把 App Store 评价变成产品研究证据：痛点、机会、版本风险和行动建议 | Agent skill for evidence-backed App Store review analysis.

Automate replies to Google Play Store reviews with OpenAI's GPT-3.5-turbo-powered Python script that fetches recent app reviews and generates responses

Manage App Store Connect from your terminal — metadata, screenshots, reviews, TestFlight, IAP, releases. A Claude Code skill.

AppPulse — 感知每一条用户心声 | 输入 App 名字，自动抓取全球 App Store & Google Play 评论，AI 多维分析，生成可视化洞察报告

Analyze App Store and Google Play reviews with an analyze-first skill for agents and API workflows.

Sample code to demonstrate how to use the Store Review Plugin in Xamarin.Forms

> End-to-end RAG pipeline that turns Google Play app reviews into a production-ready, searchable knowledge base using Thordata scrapers and embeddings.

AI-powered pipeline that transforms raw mobile game reviews into actionable product intelligence. Features LLM-based classification, priority scoring, and executive health KPIs. Built with FastAPI, Streamlit, and OpenAI to automate sentiment analysis, fraud detection, and trend tracking for game ops.

Automated app review monitoring and user feedback analysis system built with n8n, AI, and Notion

Classifier for app reviews on a scale of 1 to 5 using Gated Recurrent Unit (GRU).

Last-30-days research ranked by authenticity, not raw engagement. Scores every result for astroturf/bot signals and covers sources others skip — App Store + Play Store reviews and Pantip (Thailand). Python engine + agent skill + Next.js dashboard.

Turn Codex/ChatGPT into a HarmonyOS product-research agent: AppGallery evidence, satisfaction analysis, reports, and Android/HarmonyOS feature parity.

A sentiment analysis model for Microsoft Office app reviews, leveraging advanced text preprocessing and deep learning architectures to accurately classify user sentiments

App Store & Google Play data for Node and AI agents — typed client + MCP server for the App Intel API (RapidAPI)

This project analyzes Google Play Store app reviews using a daily batch-based AI pipeline. It extracts common user issues and feedback from reviews and generates a trend analysis report showing how these topics change over time. The system is designed to help product teams quickly identify recurring problems and emerging trends.