
Mobile Device Mcp
io.github.saranshbamania由 GitHub 帳號 saranshbamania 發布v0.2.9更新於 Oct 24, 2026
AI control of Android/iOS devices. Screenshots, UI tree, AI vision, Flutter, video. 49 tools.
概覽
一個本機 MCP 伺服器,讓 AI 程式助理透過截圖、UI 檢查與點擊輸入來檢視並控制 Android 裝置與 iOS 模擬器。
- 可以做什麼
- 擷取畫面並檢查裝置 UI 樹,包含更快的配套應用程式通道與 logcat 記錄。點擊、輸入、送出按鍵,並依描述尋找元素,可選用 AI 視覺分析、畫面差異比對與表單填寫。透過 Dart VM Service 檢查 Flutter 應用程式:元件樹、原始碼對應、元件截圖、除錯繪製、熱重載與熱重啟。管理應用程式:啟動、停止、安裝與解除安裝。錄製螢幕,並依記錄的工具呼叫產生 TypeScript、Python 或 JSON 測試腳本。在 macOS 上列出、啟動、關閉 iOS 模擬器並截圖。
- 適用情境
- 適合助理需要在已連線的 Android 裝置或模擬器、或 Flutter 應用程式上操作與驗證畫面,而不必依賴手動貼上截圖時。也適合把探索性的裝置操作轉成可重複使用的測試腳本。
- 執行需求
- 透過 npx 在本機執行,需要 Node.js 18 或更新版本。需要 ADB 以及已連線的 Android 裝置或模擬器;iOS 模擬器工具需要 macOS 與 xcrun simctl。AI 視覺工具需要 Google API 金鑰(GOOGLE_API_KEY),Claude 視覺另需 Anthropic 金鑰。Pro 授權金鑰 MOBILE_MCP_LICENSE_KEY 可解鎖完整工具集。選用變數可設定 ADB 路徑與預設裝置。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Mobile Device Mcp,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
mobile-device-mcp
[npm version] [npm downloads] [GitHub stars] [License: BSL 1.1]
MCP server that gives AI coding assistants (Claude Code, Cursor, Windsurf) the ability to see and interact with mobile devices. 49 tools for screenshots, UI inspection, touch interaction, AI-powered visual analysis, Flutter widget tree inspection, video recording, and test generation.
AI assistants can read your code but can't see your phone. This fixes that.
Why This One?
The Problem
Web developers have browser DevTools, Playwright, and Puppeteer -- AI assistants can click around, take screenshots, and verify fixes. Mobile developers? They're stuck manually screenshotting, copying logs, and describing what's on screen. They're human middleware between the AI and the device.
What This Does
Quick Start
Install
No global install needed. Runs directly via npx.
Prerequisites
- Node.js 18+
- Android device/emulator connected via ADB
- ADB installed (Android SDK Platform Tools)
Setup (One-time, 30 seconds)
-
Get a Google AI key (free tier available): aistudio.google.com/apikey
-
Add
.mcp.jsonto your project root:
macOS / Linux:
Windows:
With Pro license key (after purchasing Pro):
macOS / Linux (Pro)
Windows (Pro)
- Open your AI coding assistant from that directory. That's it.
The server starts and stops automatically -- you never run it manually. Your AI assistant manages it as a background process via the MCP protocol.
Verify It Works
Claude Code: type /mcp -- you should see mobile-device: Connected
Cursor: check MCP panel in settings
Then just talk to your phone:
No test scripts. No manual screenshots. Just describe what you want in plain English.
Works with Any AI Coding Assistant
All use the same JSON config -- just put it in the right file for your editor.
Drop Into Any Project
Copy .mcp.json into any mobile project -- Flutter, React Native, Kotlin, Swift -- and your AI assistant gets device superpowers in that directory. No global install needed.
Free vs Pro
Free (14 tools) -- no license key needed
Pro (35 additional tools) -- ₹499/mo
Get Pro License -- unlock all 49 tools. After payment, you'll receive your license key via email within 1 hour. Add it to your .mcp.json:
AI Visual Analysis (12 tools)
Use AI vision (Claude or Gemini) to understand what's on screen.
Flutter Widget Tree (10 tools)
Connect to running Flutter apps via Dart VM Service Protocol. Maps every widget to its source code location (file:line).
iOS Simulator (4 tools)
macOS only. Control iOS simulators via xcrun simctl.
Video Recording (2 tools)
Test Generation (3 tools)
App Management (4 tools)
Performance
The server is optimized to minimize latency and AI token costs:
- 4-tier element search: companion app (instant) -> local text match (<1ms) -> cached AI -> fresh AI.
smart_tapis 35x faster than naive AI calls (205ms vs 7.6s). - Companion app: AccessibilityService-based Android app provides UI tree in 105ms (23x faster than UIAutomator's 2448ms). Auto-installs on first use.
- Screenshot compression: AI tools auto-compress to JPEG q=60, 400w -- 89% smaller (251KB -> 28KB) with zero AI quality loss.
- Parallel capture: Screenshot + UI tree fetched simultaneously via
Promise.all(). - TTL caching: 5-second cache avoids redundant ADB calls for rapid-fire tool usage.
Environment Variables
Architecture
Roadmap
- iOS physical device support
- Multi-device orchestration
- CI/CD integration
- Cloud device farm support
Tested On
- Devices: Pixel 8 (Android 16), Samsung Galaxy series, Android emulators
- Apps: Telegram, Instagram, Spotify, WhatsApp, YouTube, Chrome, Settings, and Flutter apps
- AI Providers: Google Gemini 2.5 Flash, Anthropic Claude
- Platforms: Windows 11, macOS (iOS simulators)
- Connection: USB and wireless ADB
License
- Free for individuals and non-commercial use
- Commercial use requires a paid license
- Converts to Apache 2.0 on March 23, 2030
See LICENSE for full terms.
來源:README.md,提交 0c753ba
工具
0版本歷史
1- v0.2.9最新Sep 16, 2026
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