AI-powered mobile automation agent for Android and iOS. Tell it what to do in plain English — it figures out what to tap, type, and swipe.

You: "Send a WhatsApp message to Mom saying good morning" AppClaw: Step 1: Open WhatsApp Step 2: Search for Mom Step 3: Open chat with Mom Step 4: Type "good morning" Step 5: Tap Send Step 6: Done ✅ Goal completed in 6 steps.

📖 Full guide, setup, and docs → appclaw.in

npm install -g @appclaw/cli
appclaw doctor   # preflight: Node, .env, LLM key, appium-mcp, devices
appclaw "open the settings app and turn on airplane mode"

You'll need Node.js 22+, a connected device / emulator / simulator, and an LLM API key (Anthropic, OpenAI, Google, Groq, or local Ollama). appclaw doctor checks all of this in seconds and prints fix hints for anything missing (--full also spawns appium-mcp for a real handshake). Full setup → appclaw.in.

• Agent mode — plain-English goals; the LLM drives the device (tap, type, swipe)
• YAML flows — deterministic, zero-LLM automation with structured selectors and state assertions
• Test runner — vitest-style specs across real devices; scaffold with appclaw init
• SDK — drive AppClaw from your own vitest / jest / mocha
• Playground, cloud devices, record & replay, PRD explorer, and more

Every mode is documented at appclaw.in.

git clone https://github.com/appclawhq/AppClaw.git
cd AppClaw
npm install
npm run build
cp .env.example .env   # add your LLM key

See CLAUDE.md for the architecture overview, and appclaw.in for usage.

Licensed under the Apache License, Version 2.0. See LICENSE for the full text.