App Store Optimization for AI agents: keyword ranks, suggestions, popularity, competitors, reviews
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
๐ก Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Inspect callable tools, capabilities, and parameters exposed to AI agents by Openaso.
rankAn app's position in App Store search results for a keyword (top 200), per storefront.
suggestApp Store search-autocomplete suggestions for a seed term โ the terms Apple itself suggests.
volumeKeyword demand (popularity 0โ100, Apple Search Ads popularity where available) plus competition count.
competitorsTop-ranking apps for a keyword: position, ratings, genre, keyword-in-title.
appMetadata for one app per storefront, including whether it is available there.
auditOne-call ASO research bundle: current listing, indexed word pool, autocomplete-discovered keyword candidates scored for demand and competition.
openaso is a hosted MCP server that gives AI agents real App Store Optimization data from Apple's public app-store APIs: keyword ranks, search-autocomplete suggestions, keyword popularity (real Apple Search Ads popularity where available), competitor intelligence, review mining, chart positions, local metadata keyword-coverage analysis, and account-scoped daily rank tracking.
https://mcp.openaso.ai/mcp (Streamable HTTP, stateless)ai.openaso/openaso.md)This repository is the public home of openaso: connection docs, examples, and the issue tracker. The server's source code is proprietary and is not published here.
Claude Code
Any MCP client (JSON config)
Authentication is Authorization: Bearer <key> (an x-api-key header also works).
Everything is per-storefront: ranks, availability, suggestions and popularity differ by country,
so tools take an explicit countries list (default ["US"]).
| Tool | What it returns |
|---|---|
rank | An app's position in App Store search results for a keyword (top 200), per storefront. |
suggest | App Store search-autocomplete suggestions for a seed term โ the terms Apple itself suggests. |
volume | Keyword demand (popularity 0โ100, Apple Search Ads popularity where available) plus competition count. |
competitors | Top-ranking apps for a keyword: position, ratings, genre, keyword-in-title. |
app | Metadata for one app per storefront, including whether it is available there. |
audit | One-call ASO research bundle: current listing, indexed word pool, autocomplete-discovered keyword candidates scored for demand and competition. |
coverage | Which search phrases a metadata draft can rank for โ computed locally from the title/subtitle/keyword-field word pool, no network. |
reviews | Recent customer reviews from Apple's public RSS: rating distribution, average, texts. |
charts | Position on the top-free, top-paid and top-grossing charts (top 100), per storefront. |
revenue | Order-of-magnitude revenue estimate modeled from public top-grossing chart rank. |
track_config | Manage the account's tracked set of (app ร keyword ร storefront) combinations. |
track | Snapshot ranks for everything in the tracked set, on demand. |
history | Server-side rank history โ written by track and by the managed daily tracking run. |
Apple indexes an app's title (30 chars), subtitle (30) and hidden keyword field (100) as one
combined word pool โ an app can rank for any query assembled from words across those fields.
openaso's tools are built around that model: audit finds the candidates, coverage scores a
draft's pool locally, rank/volume verify against the real store. The full model is explained
in the docs (agents: llms.txt).
ยฉ 2026 Hector Lopez. All rights reserved. openaso is not affiliated with, endorsed by, or sponsored by Apple Inc. App Storeยฎ and iTunesยฎ are trademarks of Apple Inc. Data is retrieved from Apple's public endpoints; you are responsible for using it in compliance with Apple's terms.
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