
App Store Operator
io.github.meyusufdemirciPublished by GitHub account meyusufdemirciv0.3.5Updated Oct 24, 2026
Free App Store competitive intelligence for Claude — rival downloads, revenue, and ASO keywords.
Overview
An MCP server that brings iOS App Store competitive research into an assistant: keyword search, rival download and revenue estimates, and In-App Event copy.
- What you can do
- Search the App Store by keyword and country and get ranked results as a table
- Pull SensorTower analytics for rival apps or given app IDs: downloads, revenue, ratings, publisher, markets, in-app purchases
- Generate iOS In-App Event copy in three variations for a target locale, with character-limited fields
- Use six ready-made prompt workflows for competitor snapshots, keyword shortlists, app teardowns, positioning gaps, metadata rewrites and in-app events
- Read reference resources for country codes, ASO and IAE field limits, locales, and locally cached research
- When to use it
- Useful for indie iOS developers who want keyword and competitor research, ASO metadata drafts or in-app event copy inside the assistant instead of a separate dashboard. It is iOS-only and read-only, so it suits research and copywriting rather than managing App Store Connect.
- Requirements
- Node.js v18 or later; the package is run via npx and downloads a Playwright Chromium build (a few hundred MB). A desktop session with a display is needed for the two SensorTower tools, which open a visible browser window for a free SensorTower sign-in; they do not work over plain SSH or in a container. Optional environment variables ASO_CACHE_TTL_HOURS and ASO_DEBUG_RATINGS.
Installation
In SourceWeft
- Open App Store Operator in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
App Store Operator
[npm] [downloads] [license] [node] [MCP] [MCP Badge]
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.
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.
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.
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.
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).
Any field SensorTower does not expose, or keeps behind its paywall, comes back as N/A.
The server reports the gap rather than filling it, and the prompts below tell the assistant
to do the same.
Prompts
Six ready-made workflows that already chain the tools above, so you don't have to describe the sequence yourself. In Claude Code they appear as slash commands; other clients surface them in a prompt picker.
Arguments marked ? are optional. Every prompt tells the assistant not to invent figures and, where SensorTower is involved, not to quietly fall back to a weaker tool when login is required.
Resources
Reference data and local state a client can attach as context without spending a tool call on it.
Nothing here leaves your machine: the reference resources are static, and the two cache resources read ~/.app-store-operator/cache.json.
Requirements
- Node.js v18+
- A desktop session for
research_rivalsandget_app_details. They drive a real, visible Chromium window so you can sign in to SensorTower, so they need a display — they do not work over plain SSH or inside a container. The other two tools have no such requirement. - Disk space for Chromium. Installing the package downloads a Playwright Chromium
build (a few hundred MB) via a postinstall step. If that step fails, the server installs
it on first use instead; you can also run
npx playwright install chromiumyourself.
Usage
As an MCP server (Claude Code / Claude Desktop / OpenAI Codex)
Claude Code — run this command once:
Claude Desktop — add to your MCP config:
OpenAI Codex — run this command once:
Codex stores MCP servers in ~/.codex/config.toml. If you prefer to edit it directly:
Then restart Codex or start a new thread, and ask things like:
Research rivals for "hairstyle" in the GB App StoreSearch the App Store for "beard style" in FrancePrepare an in-app event for a summer hairstyle campaign in en-gb
No installation step needed — npx fetches and runs the package automatically.
The server communicates over stdio and is designed to be invoked by an MCP client. It advertises server-wide instructions during initialize so clients route between the tools correctly, and returns an MCP tool error when SensorTower login is required.
Configuration
Both settings are optional environment variables on the server process.
In a container
The repo ships a Dockerfile built on Playwright's official image:
The server speaks JSON-RPC over stdio, so no port is exposed — point your MCP client at
the container's stdin/stdout. Note that a container has no display: search_app_store
and prepare_iae work there, but the two SensorTower tools cannot open a login window and
will fail rather than prompting you to sign in.
How it works
- Searches the App Store for the keyword and country, and looks up any app IDs you passed directly against Apple's public iTunes Lookup API
- For each app, drives a Chromium browser to scrape SensorTower analytics
- Extracts the metrics and returns a compiled report
SensorTower data is scraped via Playwright because it is rendered client-side.
A browser window will open. This is deliberate, not a bug: SensorTower requires a login, so the first run opens a visible window for you to sign in. The session is saved to ~/.app-store-operator/profile and reused on every later call, so you only log in once. If a tool reports not_logged_in, finish signing in on that window and run the tool again.
Results from research_rivals are cached for 24 hours in ~/.app-store-operator/cache.json — override the TTL with the ASO_CACHE_TTL_HOURS environment variable.
Limitations
- iOS only. Nothing here covers Google Play or Android.
- Read-only. No tool changes anything in App Store Connect or on SensorTower.
research_rivalsis fixed at the top 3 results. Usesearch_app_store(up to 25) and thenget_app_detailswhen you need a wider set.- Scraping is brittle by nature. SensorTower renders its dashboard client-side and
changes its markup without notice; when it does, affected fields return
N/Auntil the selectors are updated. A single app failing never fails the whole call. - SensorTower's free tier decides what you see. Paywalled figures come back as
N/A.
Privacy Policy
Full policy: https://app-store-operator.com/privacy
App Store Operator runs entirely on your machine. There is no backend, no telemetry, and no analytics — the author collects, receives, and stores nothing about you or your usage.
What each tool sends, and where:
What is stored locally:
~/.app-store-operator/cache.json— cached results, expiring after 24 hours by default (ASO_CACHE_TTL_HOURS)~/.app-store-operator/profile— the Chromium profile holding your SensorTower session
You type your SensorTower credentials into SensorTower's own page in a browser window on your machine. The server never reads or stores your password, and the author never receives it.
Deleting everything — no request to the author, nothing to wait for:
Apple and SensorTower are independent third parties with their own policies. This project is not affiliated with either.
Project structure
Development
No build step and no linter — clone it, npm install, and run npm start to boot the
server over stdio.
The smoke test verifies the server boots and exposes everything it should. It checks
initialize (including the server instructions and the advertised version), tools/list,
prompts/list, prompts/get, resources/list, resources/templates/list, and reads
every resource, failing if one declared as JSON does not parse. It makes no network calls
and opens no browser:
Releases are tag-driven: write the notes under ## Unreleased in CHANGELOG.md, run
npm version <patch|minor|major> — which syncs the version into server.json and
manifest.json and renames that heading to the new version for you — then push with
--follow-tags. GitHub Actions runs the smoke test, publishes to npm and the MCP
registry, and creates the release from that changelog section. The bump refuses to run
while ## Unreleased is empty.
Contributions are welcome — open an issue or a pull request at github.com/meyusufdemirci/app-store-operator.
License
MIT © Yusuf Demirci
Source: README.md at commit c41dfb7
Tools
0Version history
1- v0.3.5LatestSep 16, 2026
Score
50% of the applicable checks met
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- Reached in the last 30 days25 pts
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- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
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