review-miner
Mine public App Store and Steam reviews to uncover user complaints and product opportunities.
List top charts by category/store (App Store free/paid/grossing; Steam top sellers/most played/new releases).
Search for apps/games and get their store IDs.
Fetch recent reviews for one app/game: rating mix, per-version ratings, top complaint terms, and helpful negative/positive samples.
Compare 2–8 competitors side by side to find shared weaknesses and gaps.
Run focused prompts like
find_opportunities(category → product gaps) andcompetitor_teardown(love vs hate).Filter by country and Steam language; choose markdown or JSON output.
Mines public Apple App Store reviews: fetches top charts by category (free/paid/grossing) per country, searches for apps to resolve their IDs, and pulls recent reviews with rating mix, rating per version, top complaint phrases, and most helpful review texts, plus side-by-side comparisons of 2-8 apps.
Mines public Steam reviews and store data: fetches weekly top sellers, most played, and new releases, and retrieves recent reviews for a game filtered by language, with rating breakdowns and top complaint phrases; Steam games can be compared against App Store apps.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@review-miner Compare the reviews of the top 5 finance apps in Turkey. What does every one of them get wrong?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
review-miner-mcp
Find out what users hate about your competitors. An MCP server that mines public App Store and Steam reviews so Claude (or any MCP client) can turn thousands of complaints into product opportunities.
No API keys. No scraping. One line to install.
You: What do users hate about the top health & fitness apps in Turkey?
Claude: [review_top_apps → review_compare_apps]
• Strava: the most upvoted complaints ask for Turkish. "I was going to buy
Premium but I'm deleting it because there is no Turkish support."
• OKOK (smart scale): 61% of recent reviews are negative. You have to watch
ads before the app shows your own weight.
• MAC+: login and verification-code errors ("hata veriyor") dominate.
• HUAWEI Health: can't log in after switching phones or after updates.Summarized from real tool output: Turkish App Store, 1 Oct 2026, 150 recent reviews per app.

Why
You want to know | Without it | With review-miner |
Why an app's rating dropped | Scroll reviews by hand |
|
What a whole category fails at | Read 5 apps × 500 reviews | One call compares them side by side |
Whether an idea has demand | Guess | Real complaints, with quotes and counts |
Related MCP server: partnerlens-mcp
How it works
flowchart LR
C[Claude / MCP client] -->|tool call| S[review-miner-mcp]
S --> A[Apple iTunes Search + RSS]
S --> T[Steam Store + Web API]
S --> X[Stats: rating mix, per-version rating,<br/>top complaint phrases]
X -->|compact summary + best review samples| CThe server does the cheap, deterministic part (fetching, counting, phrase extraction). The model does the interpretation. Only the most helpful review texts are returned, so your context window is not flooded.
Install
Requires uv.
Claude Code
claude mcp add review-miner -- uvx review-miner-mcpClaude Desktop / Cursor (claude_desktop_config.json / .cursor/mcp.json)
{
"mcpServers": {
"review-miner": {
"command": "uvx",
"args": ["review-miner-mcp"]
}
}
}Tools
Tool | What it does |
| Current top charts: App Store by category (free / paid / grossing) or Steam weekly top sellers / most played / new releases |
| Find an app or game and get its ID |
| Recent reviews for one app: rating mix, rating per version, top complaint phrases, most helpful texts |
| 2–8 competitors side by side, App Store and Steam mixed |
Prompts: find_opportunities (category → product gaps), competitor_teardown (one app, love vs hate).
Every tool supports country (e.g. tr, de, us) and response_format (markdown / json).
Try these
"Compare the reviews of the top 5 finance apps in Turkey. What does every one of them get wrong?"
"Did Duolingo's latest version lower its rating? Show rating by version."
"What do negative Steam reviewers of Cyberpunk 2077 complain about, and how many hours had they played?"
"Run find_opportunities for health-fitness in Germany."
Limits (set by the sources)
App Store: most recent ~500 reviews per country (Apple's feed limit).
App Store: Apple's review feed is sometimes empty for an app/country for a while. The server retries equivalent feed URLs automatically; if all are empty it tells you so instead of reporting "no reviews". Retrying a few minutes later or trying another country usually works.
Steam: most recent reviews, filtered by language (
english,turkish,all...).Results are cached for 15 minutes; concurrency is capped to stay polite.
Part of the keyless MCP series
Open-source MCP servers that answer one market question each, with public data and no API keys.
Server | Question it answers |
review-miner-mcp (this one) | What do users hate about competitor apps and games? (App Store + Steam reviews) |
How did a SaaS pricing page change over the years? (Wayback Machine) | |
Which skills are tech companies hiring for, and which are rising? (HN Who is hiring) | |
What does each LLM cost, and did it get cheaper? (OpenRouter + price history) | |
What is a company about to launch? (certificate transparency logs) |
Development
uv sync --extra dev
uv run pytest # offline tests with mocked APIs
uv run python scripts/smoke_live.py # live check against Apple and Steam
npx @modelcontextprotocol/inspector uv run review-miner-mcp # click-through UI
uv run --with rich python scripts/demo.py finance tr # terminal demo (vhs docs/demo.tape records the GIF)MIT © Ali Altunar
Available Tools
4 toolsreview_compare_appsARead-onlyIdempotent
Compare recent reviews of 2-8 competitors side by side: rating, negative share and top complaint terms per app, plus a few negative samples each. Use it to find gaps that every competitor fails at (= product opportunity).
Inputs: apps (required), country, language, response_format, +2 more. Returns: result
review_fetchARead-onlyIdempotent
Fetch recent reviews for one app/game and return stats (rating mix, rating per version, top complaint terms) plus the most helpful review texts. Best for 'why do users hate X?'.
Inputs: app_id (required), only, store, country, +4 more. Returns: result
review_search_appsARead-onlyIdempotent
Find an app/game and its ID by name. Returns IDs in 'store:id' form for the other tools.
Inputs: query (required), limit, store, country, +1 more. Returns: result
review_top_appsARead-onlyIdempotent
List the current top charts (App Store by category, or Steam top sellers / most played / new releases). Use this to pick competitors before fetching their reviews.
Inputs: chart, limit, store, country, +2 more. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool targets a distinct step or scope: chart discovery, app lookup, single-app review fetching, and multi-app comparison. There is no meaningful overlap in purpose, and the descriptions clearly distinguish when to use each.
All tools use the review_ prefix and mostly follow an action-oriented pattern. The only minor deviation is review_fetch, which omits an explicit object noun like the others, but the convention remains readable and predictable.
Four tools are well-scoped for a review-mining workflow: discover apps, resolve IDs, fetch reviews, and compare competitors. Each tool earns its place without redundancy.
The core lifecycle is covered: finding apps, retrieving reviews with stats, and comparing multiple apps. Minor gaps exist around filtering by time range or exporting raw reviews, but the surface supports the primary use cases.
Maintenance
Related MCP Connectors
App Store and Google Play reviews summarised by AI into bugs, feature requests, critical issues and competitor mentions, for product teams. Runs on Apify, $0.05 per app.
Analyze App Store and Google Play reviews: themes that cost stars, regressions, feature requests.
Read, search, analyze and draft replies to App Store and Google Play reviews (OAuth sign-in).
Limited-beta App Store and Google Play review analysis, source reviews, alerts and reply drafts.
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