Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y [email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add agent-device -- npx -y agent-device@0.21.37รันในเทอร์มินัล
{ "mcpServers": { "agent-device": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดMobile app automation and verification for AI coding agents. Give coding agents a live app feedback loop through a CLI, built-in MCP server, or typed Node.js API.
Let your coding agent verify its changes in the running app. agent-device lets agents inspect, control, debug, and verify apps on iOS, Android, and HarmonyOS (simulators, emulators, and physical devices), plus tvOS, Android TV, Fire TV (Fire OS), Amazon Vega OS TV (Vega Virtual Device), web, macOS, and Linux. Agents read token-efficient accessibility snapshots instead of reasoning over screenshots alone, act through refs and selectors, and save evidence for review. It also coordinates device access across parallel agent worktrees and connects to remote device clouds.
Works with Claude Code, Codex, Cursor, Windsurf, Cline, Goose, and any agent that can run a CLI or connect over MCP, or as the runtime under agents you build with the AI SDK or Eve. Developers at Expensify, Shopify, and others use it to verify their apps.
Install the CLI and check setup. It requires Node.js 22.12 or newer; web automation requires Node.js 24 or newer. See Installation for target requirements.
npm install -g agent-device@latest
agent-device doctor
agent-device help workflow
Run doctor yourself before you hand the CLI to an agent. help workflow links to the guides for debugging, replay, and profiling.
Add a contact in the built-in iOS Contacts app:
# Start a session.
agent-device open Contacts --platform ios
# Inspect the screen. The example below shows the output; refs vary.
agent-device snapshot -i
# @e2 [button] "Add"
# Use the ref and wait for the UI to settle.
agent-device press @e2 --settle
# The diff includes:
# + @e7 [text-field] "First name"
agent-device fill @e7 "Ada" --settle
# The next diff shows changed values and current refs:
# - @e7 [text-field] "First name"
# + @e14 [text-field] "Ada"
# = @e15 [text-field] "Last name"
# Capture evidence and close the session.
agent-device screenshot ./contact-form.png
agent-device close
Refs are valid only in the latest output: after a --settle command, use the refs in its diff, and take a new snapshot only if the diff omits what you need. Snapshots come from the app's accessibility tree, so clear labels, roles, and test IDs make agent runs more reliable; use screenshots and video as evidence or when accessibility data is poor.
agent-device mcp starts the official stdio MCP server, exposing the installed commands as structured tools over the same execution path as the CLI:
{
"mcpServers": {
"agent-device": {
"command": "agent-device",
"args": ["mcp"]
}
}
}
See AI Agent Setup for per-client setup and when to prefer plain CLI over MCP.
createAgentDeviceClient() gives Node.js code typed access to the same commands, as model tools in your own agent or from orchestration code:
import { createAgentDeviceClient } from 'agent-device';
const client = createAgentDeviceClient({ session: 'qa-run' });
try {
await client.apps.open({ app: 'com.apple.Preferences', platform: 'ios' });
const snapshot = await client.capture.snapshot({ interactiveOnly: true });
const button = snapshot.nodes.find((node) => node.role === 'button');
if (button) await client.interactions.press({ ref: button.ref });
} finally {
await client.sessions.close();
}
See the Node.js API, the runnable examples, and the AI SDK and Eve integration guides.
.ad scripts for local use or CI. Export strict Maestro YAML when needed.See Commands for the commands and evidence each target supports.
With the CLI installed, prompts like these work end to end:
The same session and evidence model works at every step: the agent explores the app, captures evidence, saves a replay, runs it in CI, and moves onto remote devices.
agent-device keeps device state in sessions. It uses a local accessibility bridge for iOS Simulator snapshots and XCTest for iOS interactions, physical iOS, and tvOS; ADB and the snapshot helper on Android, Android TV, and Fire OS; HDC and ArkUI uitest on HarmonyOS; Vega CLI/VDA on the Vega Virtual Device; a local helper on macOS, including Electron and other Chromium-based apps through the accessibility tree; and AT-SPI on Linux.
Support depth varies by target. Some backends, such as HarmonyOS and Vega OS, cover a subset of commands; run agent-device capabilities --platform <platform> to see what a target supports. The capabilities matrix shows which commands each target, desktop, web, and cloud provider supports.
Sessions are scoped to the caller's git worktree, and host-local device claims stop parallel agents from taking over each other's simulators and emulators. Run agent-device device status to inspect ownership without a daemon, and agent-device device release --stale to release claims whose owner is provably no longer running. The same commands drive hosted devices on BrowserStack, AWS Device Farm, TestMu AI, and Limrun.
agent-device uses the inspect-act-verify process from Vercel's agent-browser for mobile, TV, and desktop apps. Basic --platform web support runs agent-browser in the same session and replay system.
agent-device is a command-line tool and MCP server that lets AI coding agents inspect, control, and verify mobile apps and save evidence for review. It supports iOS, Android, HarmonyOS, TV, web, macOS, and Linux.
Yes. agent-device mcp starts the official stdio MCP server. The Quick start above has the client config, and AI Agent Setup covers per-client details.
Yes. agent-device supports native iOS and Android apps, plus React Native, Expo, and Flutter apps on supported targets. The commands and evidence vary by target.
The MCP server is one entry point to the same runtime used by the CLI and typed Node.js API. Sessions, device ownership, selectors, evidence, replay, CI workflows, and cloud routing stay consistent across all three.
Yes. The typed Node.js client is a public surface over that same runtime, so an agent you build inherits everything above. Start from the Node.js API, AI SDK, or Eve guides.
With agent-device, an agent reads app state and chooses each command at run time. Teams use Appium, Detox, and Maestro to write and maintain test suites. agent-device can complement them by saving its runs as .ad scripts or exporting them as strict Maestro YAML.
Yes. Record a run as an .ad script, replay it in CI, and keep the screenshots and logs as artifacts; the EAS workflow template is a working example.
Teams and developers at Callstack, JPMorgan Chase, Expensify, Shopify, Kindred, Total Wine & More, LegendList, HerLyfe, App & Flow, and others use agent-device.
See CONTRIBUTING.md.
agent-device is open source under the MIT license. Visit agent-device.dev or contact Callstack.
Open source device layer for AI coding agents: a CLI, MCP server, and typed Node.js API to control mobile, web, TV, and desktop apps on devices and simulators, locally or in the cloud.
{ "mcpServers": { "agent-device": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Agent Device ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-13 Open source device layer for AI coding agents: a CLI, MCP server, and typed Node.js API to control mobile, web, TV, and desktop apps on devices and simulators, locally or in the cloud.