meyusufdemirci/app-store-operator

**App Store competitive intelligence, inside Claude.**
App Store Operator is an MCP server that brings App Store research directly into your AI
assistant. Instead of switching to a dashboard, you ask Claude for ranked keyword results,
competitor download and revenue estimates, or App Store Connect-ready In-App Event copy —
and get the answer in the same conversation where you are making the decision.
Built for indie iOS developers who want research inside their workflow rather than in
another browser tab. Free and open source (MIT). A lightweight alternative to SensorTower,
AppTweak, and AppFollow for iOS-only competitive research.
→ app-store-operator.com · Setup guide
What it does
Searches the App Store for competing apps on a given keyword and pulls detailed analytics
from SensorTower — downloads, revenue, ratings, top markets, publisher info, and more.
search_app_store and prepare_iae work with no account at all. research_rivals and
get_app_details open a browser once for a **free** SensorTower sign-in, then reuse that
saved session — no paid plan, no API key.
Everything the server exposes — four tools, six prompts, seven resources — is read-only.
Nothing writes to your App Store Connect account, to SensorTower, or anywhere but a local
cache file.
Tools
research_rivals
Finds the top 3 apps for a keyword and returns a full metrics report for each.
| Parameter | Type | Description |
|-----------|------|-------------|
| keyword | string | Search term to look up (e.g. meditation, psikoloji) |
| country | string | Two-letter country code (e.g. us, tr, gb) |
**Returns for each competitor:**
- App Store & SensorTower URLs
- Worldwide and last-month downloads & revenue
- Rating score and rating count
- Publisher, categories, top markets
- Release date, last updated, supported languages
- In-app purchases and ad network presence
Cached for 24 hours, so asking again about the same keyword and country costs nothing and
opens no browser.
---
search_app_store
Searches the App Store for a keyword and returns ranked results as a markdown table — instantly, no SensorTower required.
| Parameter | Type | Description |
|-----------|------|-------------|
| keyword | string | Search term to look up |
| country | string | Two-letter country code |
| limit | number | Number of results to return (1–25, default 3) |
Use this to discover which apps rank before deciding which to analyse. Follow up with get_app_details for analytics on specific apps.
---
get_app_details
Fetches SensorTower analytics for one or more app IDs you already have.
| Parameter | Type | Description |
|-----------|------|-------------|
| app_ids | array | Numeric App Store IDs (e.g. from search_app_store) |
| country | string | Two-letter country code |
**Returns for each app:**
- Downloads and revenue (worldwide + last month)
- Rating score and rating count
- Publisher, categories, top markets
- Release date, last updated, supported languages
- In-app purchases and ad network presence
Never cached — every call scrapes fresh, at roughly 10–20 seconds per app ID.
---
prepare_iae
Generates iOS App Store In-App Event (IAE) copy — 3 variations in the target language, then a final report.
| Parameter | Type | Description |
|-----------|------|-------------|
| keywords | array | Ordered keywords by priority (index 0–2 = Tier 1, 3–6 = Tier 2, 7–9 = Tier 3) |
| locale | string | Target locale (e.g. en-us, en-gb, de-de, tr, ja, ko) |
| event_purpose | string | What the event is about and why users should care |
| audience | string | Target audience (e.g. students, professionals, parents) |
| event_context | string | Real-world hook tying the event to a moment (e.g. a holiday, season) |
| goal | string | Primary conversion goal (e.g. attract new users, boost engagement) |
| tone | string | Copy tone: Engaging, Playful, Motivational, Authoritative, Calm, or Urgent |
**Returns:** a structured brief used to generate 3 copy variations, each with event name (≤30 chars), short description (≤50 chars), and long description (≤120 chars).