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openaso-mcp

connector

xekor

App Store Optimization for AI agents: keyword ranks, suggestions, popularity, competitors, reviews

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0 starsSynced Aug 2, 2026

Install to Claude Code

/plugin marketplace add xekor/openaso-mcp

README

openaso — App Store Optimization for AI agents

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.

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.

Quick start

  1. Create a free account and mint an API key at https://openaso.ai (free tier: 500 tool calls/day, 500 tracked app × keyword × storefront combinations).
  2. Connect your client.

Claude Code

claude mcp add openaso --transport http https://mcp.openaso.ai/mcp \
    --header "Authorization: Bearer YOUR_KEY"

Any MCP client (JSON config)

{
  "mcpServers": {
    "openaso": {
      "url": "https://mcp.openaso.ai/mcp",
      "headers": { "Authorization": "Bearer YOUR_KEY" }
    }
  }
}

Authentication is Authorization: Bearer <key> (an x-api-key header also works).

Tools

Everything is per-storefront: ranks, availability, suggestions and popularity differ by country, so tools take an explicit countries list (default ["US"]).

ToolWhat it returns
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 — the terms Apple itself suggests.
volumeKeyword demand (popularity 0–100, 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.
coverageWhich search phrases a metadata draft can rank for — computed locally from the title/subtitle/keyword-field word pool, no network.
reviewsRecent customer reviews from Apple's public RSS: rating distribution, average, texts.
chartsPosition on the top-free, top-paid and top-grossing charts (top 100), per storefront.
revenueOrder-of-magnitude revenue estimate modeled from public top-grossing chart rank.
track_configManage the account's tracked set of (app × keyword × storefront) combinations.
trackSnapshot ranks for everything in the tracked set, on demand.
historyServer-side rank history — written by track and by the managed daily tracking run.

Why agents like it

Apple indexes an app's title (30 chars), subtitle (30) and hidden keyword field (100) as one combined word pool — 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).

Support

Legal

© 2026 Hector Lopez. All rights reserved. openaso is not affiliated with, endorsed by, or sponsored by Apple Inc. App Store® and iTunes® 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.

Rendered live from xekor/openaso-mcp's GitHub README — not stored, always reflects the source repo.

1 Install Method

NameDescriptionCategorySource
streamable-http remoteHosted streamable-http endpointmcp-serverhttps://mcp.openaso.ai/mcp

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