App Store Optimization for AI agents. Connect Claude Code, Cursor, Codex or any MCP client to your App Store rankings, keywords, competitors and reviews.
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 → 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 → Developer → Edit Config, then add:
Save as .cursor/mcp.json in your project, or ~/.cursor/mcp.json to make it available everywhere:
To keep the key out of the file, use codex mcp add with --bearer-token-env-var ASOHAWKAPIKEY instead.
Gemini CLI, VS Code and any other MCP client
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:
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/prodocik--asohawk.html)
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