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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.

Top 5 Turkish health & fitness apps compared by review-miner

Why

You want to know

Without it

With review-miner

Why an app's rating dropped

Scroll reviews by hand

rating_by_version shows which update broke it

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| C

The 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-mcp

Claude Desktop / Cursor (claude_desktop_config.json / .cursor/mcp.json)

{
  "mcpServers": {
    "review-miner": {
      "command": "uvx",
      "args": ["review-miner-mcp"]
    }
  }
}

Tools

Tool

What it does

review_top_apps

Current top charts: App Store by category (free / paid / grossing) or Steam weekly top sellers / most played / new releases

review_search_apps

Find an app or game and get its ID

review_fetch

Recent reviews for one app: rating mix, rating per version, top complaint phrases, most helpful texts

review_compare_apps

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)

pricing-time-machine-mcp

How did a SaaS pricing page change over the years? (Wayback Machine)

hn-hiring-trends-mcp

Which skills are tech companies hiring for, and which are rising? (HN Who is hiring)

model-price-radar-mcp

What does each LLM cost, and did it get cheaper? (OpenRouter + price history)

launch-detector-mcp

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 tools
review_compare_appsA
Read-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_fetchA
Read-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_appsA
Read-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_appsA
Read-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

    A3.9/5.0

    Scored across 4 tools

    Disambiguation5/5

    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.

    Naming Consistency4/5

    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.

    Tool Count5/5

    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.

    Completeness4/5

    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

    ActivitySlowing
    ResponsivenessOutdated data

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