DroidPilot

Stable Android device automation for AI agents via Accessibility Service + MCP (Model Context Protocol).

Control any Android device from Claude, ChatGPT, or any MCP-compatible AI — no ADB, no USB, no screen mirroring. Just WiFi.

DroidPilot uses Android's native Accessibility Service to directly access the UI tree and perform gestures through OS APIs. This is fundamentally more reliable than ADB-based or OCR-based approaches used by other mobile automation tools.

Key Features

• No ADB required — communicates over WiFi via WebSocket
• Native UI tree access — no screenshot OCR or computer vision needed
• Reliable gesture execution — taps, swipes, and text input via OS APIs
• MCP native — works with Claude Desktop, Claude Code, and any MCP client
• 18 automation tools — tap, swipe, type, screenshot, find element, and more
• Low token cost — structured UI data instead of expensive image analysis
• Simple setup — install APK, enable service, connect

How It Works

┌──────────────┐     MCP/stdio     ┌──────────────┐    WebSocket    ┌──────────────────┐
│  AI Agent    │ ◄──────────────► │  MCP Server  │ ◄────────────► │  Android Device  │
│  (Claude,    │                   │  (Node.js)   │    WiFi/LAN    │  (Accessibility   │
│   ChatGPT)   │                   │              │                │   Service + WS)   │
└──────────────┘                   └──────────────┘                └──────────────────┘

Why DroidPilot?

Approach	Reliability	Speed	LLM Token Cost	Setup
ADB-based (droidrun etc.)	Low — connection drops, limited UI access	Medium	High (screenshot analysis)	USB/WiFi ADB
Screen mirroring + OCR	Low — OCR errors, high latency	Slow	Very High	Complex
DroidPilot (Accessibility Service)	High — native OS integration	Fast	Low (structured data)	Install APK

Available MCP Tools

Tool	Description
connect	Connect to Android device by IP
disconnect	Disconnect from device
get_device_info	Device manufacturer, model, screen size, Android version
screenshot	Capture screen as base64 JPEG image
get_ui_tree	Full UI hierarchy with all element properties
find_element	Search elements by text, ID, class, content description
tap	Tap at screen coordinates
long_press	Long press at coordinates
swipe	Swipe gesture from point A to B
scroll	Scroll in a direction (up/down/left/right)
pinch	Pinch zoom in/out
type_text	Append text to currently focused input
set_text	Replace text in focused input
press_key	System keys: back, home, recents, notifications, etc.
click_element	Find and click element by text/ID (more reliable than coordinates)
wait_for_element	Wait for element to appear on screen (with timeout)
open_app	Launch app by package name
get_focused	Get info about currently focused input element

Quick Start

1. Android APK

Requirements: Android 11+ (API 30+), WiFi (same network as PC)

cd android
./gradlew assembleDebug
adb install app/build/outputs/apk/debug/app-debug.apk

Or open android/ in Android Studio and build from there.

Then on the device:

1. Open DroidPilot app
2. Tap "Open Accessibility Settings"
3. Enable "Mobile MCP Pro"
4. Return to app, tap "Start Server"
5. Note the IP address displayed

2. MCP Server

cd mcp-server
npm install
npm run build

3. Configure Your AI Client

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "droidpilot": {
      "command": "node",
      "args": ["/path/to/droidpilot/mcp-server/dist/index.js"]
    }
  }
}

Claude Code — add to MCP settings:

{
  "mcpServers": {
    "droidpilot": {
      "command": "node",
      "args": ["/path/to/droidpilot/mcp-server/dist/index.js"]
    }
  }
}

4. Use It

Tell the AI:

Connect to my Android device at 192.168.1.100

Then give natural language commands:

Take a screenshot of the current screen
Open Chrome and navigate to google.com
Find the search bar and type "hello world"
Scroll down the page
Press the back button

Protocol

Communication between MCP Server and Android uses JSON over WebSocket:

Request:

{
  "id": "req_1_1234567890",
  "command": "tap",
  "params": { "x": 500, "y": 1000 }
}

Response:

{
  "id": "req_1_1234567890",
  "success": true,
  "data": { "action": "tap(500.0, 1000.0)" }
}

Use Cases

• AI-powered mobile testing — let AI agents run QA flows on real devices
• Mobile RPA — automate repetitive tasks across any Android app
• Accessibility automation — build assistive workflows for users
• App monitoring — periodic screenshots and UI state checks
• Cross-app workflows — orchestrate actions across multiple apps

Security

• WebSocket runs on local network only (no internet exposure)
• Optional auth token support for WebSocket connections
• No data is sent to external servers
• All communication stays between your PC and your device on your LAN

Tech Stack

• Android: Kotlin, AccessibilityService, Java-WebSocket
• MCP Server: TypeScript, Node.js, @modelcontextprotocol/sdk
• Communication: WebSocket (JSON protocol)

Contributing

Contributions are welcome! Feel free to open issues and pull requests.

License

MIT