App Pain API
RemoteAbout App Pain API
App Pain API is a review-intelligence service for product teams and agents researching iOS and Android apps. It groups low-rated reviews into ranked pain points with evidence, and also provides trends, release history, app details, and review access.
Key features
- 01Search apps across both stores
- 02Cluster negative reviews with evidence
- 03Compare pain-point trends
- 04Inspect ratings by release
- 05Retrieve reviews and app metadata
- 06Monitor competitors with alerts
Use cases
- 01Find recurring complaints about an app
- 02Check whether user complaints are changing
- 03Identify a release associated with rating shifts
- 04Receive alerts about competitor complaints
MCP support
Provides MCP clients with read-only tools for app search, review analysis, trend comparisons, version history, reviews, details, and competitor monitoring. It also includes two prompts for app review reports.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://app-pain-api.quiet-delta.workers.dev/mcpclaude mcp add --transport http apppainapi-app-pain-api https://app-pain-api.quiet-delta.workers.dev/mcp{"mcpServers":{"apppainapi-app-pain-api":{"type":"http","url":"https://app-pain-api.quiet-delta.workers.dev/mcp"}}}Open in Cursor{"servers":{"apppainapi-app-pain-api":{"type":"http","url":"https://app-pain-api.quiet-delta.workers.dev/mcp"}}}Open in VS Code{"mcpServers":{"apppainapi-app-pain-api":{"type":"http","url":"https://app-pain-api.quiet-delta.workers.dev/mcp"}}}{"mcpServers":{"apppainapi-app-pain-api":{"serverUrl":"https://app-pain-api.quiet-delta.workers.dev/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://app-pain-api.quiet-delta.workers.dev/mcpAuth requiredTools
Details
From the project READMEApp Pain API
What users hate about any iOS/Android app — clustered complaints, evidence quotes, trends. One MCP server, no API key.
Live server · Docs · OpenAPI 3.1 · Pain index (101 apps) · Pricing
Review intelligence for any app on the App Store or Google Play — not just your own. Feed it an app id, a store link, or a bare package name; get back ranked pain-point clusters mined from real 1–2★ reviews, each with its share of complaints, a severity score, and verbatim evidence.
Built for competitive research and agent workflows: one tool call replaces a week of reading reviews by hand.
{
"painPoints": [
{ "rank": 1, "title": "Intrusive ads & ad frequency", "sharePercent": 16, "severity": 4 },
{ "rank": 2, "title": "Shadowbanning & algorithm suppression", "sharePercent": 12, "severity": 4 }
],
"overview": "Monetization pressure (ads) and opaque algorithm changes dominate complaints."
}
↑ real output — TikTok, US App Store. Cached analyses return instantly; ~100 popular apps are pre-analyzed and always free to read.
The tools
| Tool | What it does |
|---|---|
search_apps ★ | Find apps on both stores (merged results, rich fields) — the step 1 of every teardown |
mine_app_pain_points ★ | The core tool: fetch recent reviews, keep the negative ones, cluster them into ranked pain points with evidence quotes |
get_pain_trend | Compare two snapshots: what got worse, what got fixed (new / resolved / rising / falling) |
get_version_history | Rating per release — catch the version that broke things |
get_app_reviews | Raw reviews, unified schema across stores (dev replies, thumbsUp) |
get_app_details | Metadata: rating histogram, category, price, IAP |
watch_competitors | Paid: push new 1–2★ reviews and rising pain points to Slack/Discord/webhooks |
Also ships two prompts (competitor_pain_report, app_pain_deep_dive) so an agent can run a full teardown from one sentence.
Install
Server URL — paste it into any MCP client, no key needed:
https://app-pain-api.quiet-delta.workers.dev/mcp
| Client | How |
|---|---|
| Claude Code | claude mcp add --transport http app-pain-api https://app-pain-api.quiet-delta.workers.dev/mcp |
| Claude Desktop / claude.ai | Settings → Connectors → Add custom connector → paste the URL |
| ChatGPT | Settings → Apps & Connectors → Developer mode → Create → paste the URL, auth: No authentication |
| Cursor | ~/.cursor/mcp.json → {"mcpServers":{"app-pain-api":{"url":"https://app-pain-api.quiet-delta.workers.dev/mcp"}}} |
| VS Code | code --add-mcp '{"name":"app-pain-api","type":"http","url":"https://app-pain-api.quiet-delta.workers.dev/mcp"}' |
| Windsurf | ~/.codeium/windsurf/mcp_config.json → {"mcpServers":{"app-pain-api":{"serverUrl":"…/mcp"}}} |
| Codex CLI | ~/.codex/config.toml → [mcp_servers.app-pain-api] url = "…/mcp" |
| Gemini CLI | ~/.gemini/settings.json → {"mcpServers":{"app-pain-api":{"httpUrl":"…/mcp"}}} |
| stdio-only clients | npx -y mcp-remote https://app-pain-api.quiet-delta.workers.dev/mcp |
Keyless limits: unlimited cached results plus a few new analyses per day. Want your own quota (10/month free, more on paid tiers)? Register at POST /v1/register and add an x-api-key header. When the server-side allowance runs out, mine_app_pain_points degrades gracefully — it hands your agent the prepared negative reviews to cluster with its own model.
Mainland China:
*.workers.devneeds a system proxy or TUN mode to connect.
Try asking your agent
- "What do users hate most about Duolingo, and is it getting better?"
- "Compare the top 4 habit-tracker apps' pain points and find a product gap."
- "Watch my 3 biggest competitors and alert our Slack when their users start complaining about something new."
Also a plain REST API
Everything the MCP server does is available over REST with JSON responses and a full OpenAPI 3.1 spec — same cache, same quota, one GET:
curl -s "https://app-pain-api.quiet-delta.workers.dev/v1/apps/ios/835599320/painpoints"
Pricing
Free tier forever (no credit card) · Starter $9/mo (any country, 500-review depth, watch 2 competitors) · Pro $29/mo (daily alerts for 15 competitors, unlimited analyses) — details on the site.
Notes
- Data comes from public app-store pages, normalized into one schema. Not affiliated with Apple or Google.
- All tools are read-only (
readOnlyHintannotations set). - Cold analyses take 30–120s and stream progress notifications; repeat calls hit a 7-day cache and return in milliseconds.
- Privacy · Terms · Acceptable use
- Contact: [email protected]
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