What users hate about ANY iOS/Android app: clustered complaints, evidence, trends. No key needed.
Scored across 7 tools
Each tool maps to a distinct step in the workflow: search_apps for discovery, get_app_details for metadata, get_app_reviews vs mine_app_pain_points for raw vs clustered reviews, get_pain_trend for temporal deltas, get_version_history for per-release stats, and watch_competitors for monitoring. Descriptions explicitly cross-reference each other (e.g. 'use for drill-down after mine_app_pain_points'), eliminating boundary confusion.
All names use snake_case with a leading verb (get_, search_, mine_, watch_), which is predictable and readable. Minor deviation: some use the get_app_* prefix while get_pain_trend and get_version_history drop the 'app' qualifier, and 'mine' is an outlier verb style.
Seven tools is well within the ideal 3-15 range, and each earns its place by covering a distinct stage of app/competitor research. Nothing feels padded or missing at the count level.
The surface covers discovery, metadata, raw reviews, clustered pain points, trends, version history, and ongoing monitoring — a full lifecycle for app pain-point research. A notable gap is head-to-head multi-app comparison or category/ranking exploration, which agents doing competitive research would likely want.
App metadata: name, developer, category, price, average rating, rating count and 1-5★ histogram (when available).
Inputs: appId (required), store, country.
Fetch raw app reviews (unified schema across stores: rating/title/body/version/date/devReply/thumbsUp), 50 per page. Use for drill-down after mine_app_pain_points.
Inputs: appId (required), page, sort, store, +1 more.
How an app's pain points changed over time: compares two archived analyses and labels each theme new / resolved / rising / falling / stable with share deltas (percentage points). Instant (archive read, no LLM). Default: latest vs ~30 days earlier. Returns a note when the app has fewer than two snapshots yet.
Inputs: appId (required), to, from, store.
Per-version review stats (review count, average rating, first/last seen) — spot a rating crash right after a bad release. Android: aggregated from recent reviews. iOS: current version + release notes.
Inputs: appId (required), store, country.
THE core tool: fetch recent reviews of any iOS/Android app, keep the negative ones, and cluster them into ranked pain points (title, sharePercent, severity 1-5, verbatim evidence quotes). Ideal for competitive research and product discovery. Cached 7 days (instant on repeat); a COLD server-side analysis takes 30-120s. If the result has "mode":"agent", it contains prepared negative reviews and "instructions" — do the clustering yourself and present it to the user.
Inputs: appId (required), model, store, analyze, +3 more.
Search the iOS App Store and Google Play (both merged by default) to find apps and their ids. Use this FIRST when you only know an app name or a category.
Inputs: q (required), limit, store, country.
Continuous competitor monitoring (paid plans: Starter 2 apps weekly, Pro 15 apps daily). Manage the watchlist and the alert destination; digests of NEW 1-2★ reviews and NEW/RISING pain points are pushed to a Slack / Discord / any https webhook. action: list | add | remove | set_webhook | test.
Inputs: action (required), appId, store, webhookUrl.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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App Store + Google Play reviews: top complaints, what got worse by version, cross-store comparisons.
Analyze App Store and Google Play reviews: themes that cost stars, regressions, feature requests.
App Store & Google Play reviews with AI themes, bugs, and competitor reports.
Top complaint themes in 1-star reviews of 531 App Store, Google Play and Shopify apps. Read-only.
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