
Mobile Device Mcp
io.github.saranshbamania由 GitHub 账号 saranshbamania 发布v0.2.9更新于 Oct 24, 2026
AI control of Android/iOS devices. Screenshots, UI tree, AI vision, Flutter, video. 49 tools.
概览
一个本地 MCP 服务器,让 AI 编程助手通过截图、UI 检查和点击输入来查看并控制 Android 设备与 iOS 模拟器。
- 可以做什么
- 截取屏幕并检查设备 UI 树,包括更快的配套应用通道和 logcat 日志。点击、输入、发送按键,并按描述查找元素,可选 AI 视觉分析、界面差异对比和表单填写。通过 Dart VM Service 检查 Flutter 应用:控件树、源码映射、控件截图、调试绘制、热重载与热重启。管理应用:启动、停止、安装和卸载。录制屏幕,并根据记录的工具调用生成 TypeScript、Python 或 JSON 测试脚本。在 macOS 上列出、启动、关闭 iOS 模拟器并截图。
- 适用场景
- 适合助手需要在已连接的 Android 设备或模拟器、或 Flutter 应用上操作和验证界面,而不必依赖手动粘贴截图时。也适合把探索性的设备操作转成可复用的测试脚本。
- 运行要求
- 通过 npx 在本地运行,需要 Node.js 18 或更高版本。需要 ADB 以及已连接的 Android 设备或模拟器;iOS 模拟器工具需要 macOS 和 xcrun simctl。AI 视觉工具需要 Google API 密钥(GOOGLE_API_KEY),Claude 视觉另需 Anthropic 密钥。Pro 许可证密钥 MOBILE_MCP_LICENSE_KEY 可解锁完整工具集。可选变量用于设置 ADB 路径和默认设备。
安装
在 SourceWeft 中
- 打开 控制台中的 Mobile Device Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
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.
来源:README.md,提交 0c753ba
工具
0版本历史
1- v0.2.9最新Sep 16, 2026
评分
已满足适用检查项的 40%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
请在仓库或注册中心条目中声明许可证。