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callstackincubator/agent-device

callstackincubator/agent-device

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官方说明le app automation and verification for AI coding agents" agent-device Mobile 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.
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收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
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收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
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综合分 703 · 7 个来源 · mcp
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以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

agent-device
**Mobile 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, 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.
agent-device powers mobile automation in
e2e
and
T3 Code .
Quick start
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.
Run doctor yourself before you hand the CLI to an agent. help workflow links to the guides for debugging, replay, and profiling.
Drive an app from the CLI
Add a contact in the built-in iOS Contacts app:
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.
Add MCP tools to your agent
agent-device mcp starts the official stdio MCP server, exposing the installed commands as structured tools over the same execution path as the CLI:
See AI Agent Setup for per-client setup and when to prefer plain CLI over MCP.
Script it from Node.js
createAgentDeviceClient() gives Node.js code typed access to the same commands, as model tools in your own agent or from orchestration code:
See the Node.js API, the runnable examples, and the AI SDK and Eve integration guides.
What agents can do
- **Inspect app state** through accessibility snapshots, refs, and selectors, and profile React Native renders to find what makes an interaction slow.
- **Act on visible UI** by tapping or pressing elements, filling fields, scrolling, making gestures, waiting, asserting state, and handling alerts.
- **Diagnose failures** with screenshots, video, logs, traces, network data, performance samples, crash details, and React profiles.
- **Repeat workflows** by saving working steps as .ad scripts for local use or CI. Export strict Maestro YAML when needed.
See Commands for the commands and evidence each target supports.
What to ask your agent
With the CLI installed, prompts like these work end to end:
- "Implement the onboarding screen, run it on the iOS simulator and Android emulator, and attach screenshots."
- "Reproduce this crash and capture the logs that lead up to it."
- "Check whether this change causes unnecessary React Native re-renders."
- "Explore the checkout flow once, save it as a replay script, and run it in CI."
- "Verify this pull request on a physical device and attach reviewable evidence."
Next steps
- AI Agent Setup: skills, project rules, and per-client setup for Cursor, Codex, Claude Code, Windsurf, and others.
来源
awesome · https://github.com/callstackincubator/agent-device
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