ASO analytics and App Store optimization tools for indie iOS developers and AI agents.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
App Store Optimization, built for AI agents.
ASOHawk is an ASO platform your AI agent uses directly. It speaks MCP, the protocol Claude Code, Claude Desktop, Cursor, Codex and most agent CLIs already understand. Point an agent at it once and it reads your App Store rankings, keywords, competitors, reviews and revenue, and manages tracking and metadata on request.
The web dashboard exists too, but the agent is a first-class citizen, not an afterthought: every capability is a versioned tool with an explicit contract, honest limitations, and a safety model where anything that touches your App Store listing waits for your approval.
The server is remote MCP over HTTPS. Nothing to install, nothing to run, no local database: one config block in your client and the agent is connected.
1. Create a key. Sign up at asohawk.cc (free plan, no credit card), then open Settings β API keys and create a key. Read by default; add write to let the agent manage tracking.
2. Connect. For Claude Code, run once in any terminal:
Settings β Developer β Edit Config, then add:
Save as .cursor/mcp.json in your project, or ~/.cursor/mcp.json to make it available everywhere:
Add to ~/.codex/config.toml:
To keep the key out of the file, use codex mcp add with --bearer-token-env-var ASOHAWK_API_KEY instead.
Add to ~/.qwen/settings.json:
Gemini CLI takes the same httpUrl block as Qwen Code in ~/.gemini/settings.json. VS Code takes a servers block in .vscode/mcp.json. Any client that reads mcp.json works with the standard shape:
Exact snippets for every client, plus a stdio bridge for clients without remote MCP support, are in the getting started guide.
3. Ask. The agent calls ASOHawk and answers in plain language:
Give me a growth report for my apps this week.
Who are my top competitors and which keywords do they rank for that I don't?
Find new keyword opportunities for my app and track the best ones.
How many downloads and how much revenue does https://apps.apple.com/us/app/duolingo/id570060128 get?
64 tools cover the full ASO loop: rankings and keyword tracking, competitor discovery and monitoring, review streams, ASO health and recommendations, acquisition and retention funnels, revenue, keyword difficulty and popularity scoring, exact Apple Search Ads popularity on demand, chart moves, hypotheses and learnings, App Store Connect metadata edits, screenshot changes, native A/B tests (Product Page Optimization), paid-app, IAP and subscription repricing (one territory or a purchasing-power matrix across all 175), build attachment and App Review submission.
Every tool returns the same envelope: the answer under data, plus data_freshness, honest limitations, recommended_next_capabilities and a cost_class. Agents do not guess what a number means or what to call next; the response says so.
Lists inside data are tabular β {columns, rows} with positional cells β so a field name is written once, not once per row; the server states that reading rule in its instructions. Connecting with ?profile=core (or ?profile=keywords,changes) lists fewer tools up front without changing what the key may call: list_capabilities still names everything, marking what the profile left out.
Details in concepts.
ASOHawk is a hosted service; this repository is its public documentation. Found a gap or want a tool that is missing? Open an issue.
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