Let AI assistants and test suites use real phones like a human.

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Live Demo: Setup driving routes and calculate total durations in Google Maps, then open YouTube to play a Coldplay song.

Key Highlights

• Cross-App Automation & Autonomous AI Assistant: Operates not just as a robust testing framework, but as an autonomous agent capable of handling complex cross-app workflows and daily tasks via natural language;
• Zero-Maintenance Test Automation: Built upon a "Dynamic-First, Coordinate-Fallback" multimodal locating engine, eliminating fragile XPath/ID selector maintenance and remaining resilient to UI redesigns, system updates, and resolution drift;
• One-Click Bug Repro & Logcat Diagnostics in IDE: Native Model Context Protocol (MCP) integration allows Antigravity, Claude Code, and Windsurf to drive physical test devices via natural language, automatically capturing crash stacks from Logcat and keyframe screenshots;
• Ultra-Fast Execution (3–5s per Step): Pioneered an Optimistic Asynchronous Pipeline that completely decouples UI interaction from heavy LLM reasoning, achieving rapid regression throughput in Flash mode;
• Popup Self-Healing & 10+ Hour Exploration: Proprietary Safety Net double-checks targets before action execution to intercept and clear interfering system popups; Pro mode supports 10+ hours of continuous exploratory & monkey-plus stability testing;
• Industry-Leading SOTA: Achieved 99%+ task completion on Google Research's AndroidWorld benchmark (100+ complex multi-step tasks).

Antigravity × ARTEMIS: Autonomous Testing Workflow

Experience seamless collaboration between Antigravity and ARTEMIS via native MCP integration — taking you from a natural language requirement to a production-grade diagnostic report in four automated steps:

1. Prompt Input (Task Dispatch) Describe your test scenario and target metrics in Antigravity	2. Test Plan Generation Formulates a step-by-step test plan & architecture for review
3. Autonomous Test Execution Drives real device, navigates UI, and profiles performance	4. Comprehensive Final Report Delivers structured audit findings, metric tables, and raw datasets

Quick Start

Ensure an Android device (with USB Debugging enabled) or emulator is connected. The one-click startup script will automatically:

• Install System Toolchains: Detect and auto-install ADB, scrcpy, FFmpeg, and Python (uv) dependencies.
• Mount Global MCP Server & AI Agent Rules: Prompt to automatically install global MCP configurations and the Artemis Mobile Testing Mindset (rules.md) into your AI IDEs (Antigravity, Cursor, Claude Code, Codex, Windsurf, VS Code, Cline/Roo, OpenClaw).

macOS and Linux

# 1. Clone repo & navigate to directory
git clone https://github.com/google/artemis.git && cd artemis

# 2. One-click launch
./start.sh

Windows PowerShell

# 1. Clone repo & navigate to directory
git clone https://github.com/google/artemis.git
cd artemis

# 2. One-click launch
.\start.bat

PowerShell does not search the current directory for executable scripts by default, so use .\start.bat without a trailing \. In Command Prompt (CMD), use start.bat instead.

Tip: Opens http://localhost:8000 in your default browser with a device connection wizard, live screen mirroring, prompt sandbox, and execution replays. You can also run directly from CLI: uv run artemis run "Open Settings, find Battery and tell me current level" --profile flash.

MCP Setup for Codex / Antigravity / Claude Code / Windsurf (Click to expand)

ARTEMIS includes a native Model Context Protocol (MCP) server. Connect your real phone directly into AI IDEs:

1. One-Click Auto Install (Recommended)

Running ./start.sh (macOS/Linux) or .\start.bat (Windows PowerShell) will prompt you to configure global MCP and testing rules for detected IDEs (or you can install/update anytime later manually using the commands below):

# Auto-install MCP server & global rules for Antigravity / Jetski:
uv run artemis mcp --install antigravity

# Or install for all supported AI IDEs (including Codex):
uv run artemis mcp --install all

Tip: You can also configure MCP interactively during first-time setup via uv run artemis init. Pro Tip: If you want to use the artemis command globally without uv run in any directory, run uv tool install -e . once in the project root.

2. Manual Configuration (Optional)

If you prefer to configure manually, run uv run artemis mcp --generate-config <client> (for example, codex or antigravity) to output the appropriate TOML or JSON snippet. Replace /path/to/artemis with your actual repo path and point command to your .venv Python executable:

• Codex (~/.codex/config.toml):

[mcp_servers.artemis]
command = "/path/to/artemis/.venv/bin/python"
args = ["-m", "mcp_server"]
cwd = "/path/to/artemis"

[mcp_servers.artemis.env]
PYTHONUNBUFFERED = "1"
PYTHONPATH = "/path/to/artemis"

• Antigravity (~/.gemini/jetski/mcp_config.json):

{
  "mcpServers": {
    "artemis": {
      "command": "/path/to/artemis/.venv/bin/python",
      "args": ["-m", "mcp_server"],
      "cwd": "/path/to/artemis",
      "env": {
        "PYTHONUNBUFFERED": "1"
      },
      "tools": {
        "mobile_run_task": { "eager": true },
        "mobile_manage_task": { "eager": true },
        "mobile_get_device_state": { "eager": true },
        "mobile_inspect_trace": { "eager": true }
      }
    }
  }
}

• Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "artemis": {
      "command": "/path/to/artemis/.venv/bin/python",
      "args": ["-m", "mcp_server"],
      "cwd": "/path/to/artemis"
    }
  }
}

3. Mount Behavioral Rules for AI Agents (Highly Recommended)

To ensure your AI coding assistant acts with the rigor of a senior mobile test engineer and never hallucinates UI interactions, we provide a dedicated testing mindset rules file at mcp_server/rules.md (covering Active Exploration before coding, Flash vs. Pro routing strategy, Latency & Timing compensation, and the "Dynamic-First, Coordinate-Fallback" locator pattern).

You can mount or copy mcp_server/rules.md into your AI IDE's rule configuration:

• Antigravity: Add the contents of rules.md to your Workspace Rules, Global Rules settings, or agent instructions.
• Claude Code: Copy or include the contents of rules.md in your project's CLAUDE.md file.
• Cursor: Copy the contents into .cursorrules or create a rule file at .cursor/rules/artemis.mdc.
• Codex: Add the contents to ~/.codex/AGENTS.md (or the active AGENTS.override.md).
• Windsurf / OpenClaw: Add the rules to your workspace rules or global system prompts.

For more details on the testing mindset and MCP architecture, see the MCP Server README.

4. Prompt Your Phone in the IDE Chat

In Codex, Antigravity, or Claude Code, simply prompt:

"Build the latest changes into an APK, install it on the connected device, open the login screen with a test account, verify if there are any unexpected popups after login, and return screenshots of the final page."

Python SDK Integration (Click to expand)

Embed the mobile automation engine into your Python workflows in just a few lines:

import asyncio
from artemis import ArtemisClient, ConcurrencyMode


async def main():
    # 1. Initialize client with optional device targeting and concurrency strategy:
    # - concurrency_mode="per_device" (default): 1 task per device, allows multi-device parallel execution
    # - concurrency_mode="global": 1 task globally across all devices
    client = ArtemisClient(
        device_serial="emulator-5554",  # optional: target specific device serial
        default_profile="flash",        # "flash" (fast reactive) or "pro" (deep reasoning)
        concurrency_mode="per_device",  # or ConcurrencyMode.GLOBAL
    )

    # 2. Execute natural language end-to-end test case (can also override device per-run)
    result = await client.run(
        "Open System Settings, go to 'Battery', verify battery percentage is displayed, and check for any crash dialogs.",
        device_serial="emulator-5554",  # optional: override target device for this specific run
    )

    # 3. Structured assertions & execution tracing
    assert result.status == "SUCCESS", f"Test failed: {result.error}"
    print(f"✅ Test Passed! Device: {result.device_id} | Turns: {result.turns} | Trace ID: {result.trace_id}")


if __name__ == "__main__":
    asyncio.run(main())

Usage Modes

_{Console Overview: ① View Switcher (Home / Workspace) · ② Model & Replay (Flash/Pro status & video replay) · ③ Live Agent Stream (Action perception, target coordinates & structured results) · ④ Prompt Dock (Natural language dispatch) · ⑤ Task Queue & Dashboard (Lifecycle & history)}

• Web Visual Test Console (uv run artemis ui): Real-time screen projection and interactive panel, supporting natural language test dispatch, live reasoning telemetry, action trajectories, and execution replay; manage server lifecycle anytime from any terminal using uv run artemis restart, uv run artemis stop, and uv run artemis status;
• Native MCP Protocol (IDE Collaboration): Operates as a standard MCP server seamlessly integrating with Antigravity, Claude Code, Windsurf, etc., directly driving real devices inside the IDE to verify bugs and run test cases;
• Developer CLI (uv run artemis run): Direct terminal execution for automated test cases, exploratory stability inspection, or AndroidWorld benchmarks with high-fidelity structured terminal output;
• Python SDK: Integrates as a standard Python library into existing automated testing frameworks (e.g., pytest) or CI/CD pipelines with strongly typed Pydantic structured outputs and assertion support.

Benchmarks: AndroidWorld (SOTA 99%+)

Evaluated on AndroidWorld — Google Research's gold-standard benchmark spanning 20+ real apps and 100+ complex multi-step tasks: Artemis demonstrated exceptional robustness across the entire benchmark suite, achieving a 99%+ completion rate.

How ARTEMIS is Architected

• Pre-Touch Pixel Gate & Speculative Chaining: Eliminates "silent misclicks" from inference latency race conditions. Milliseconds before dispatch, a local UI guard intercepts unexpected dialogs (0 tokens, 0 cloud wait), a Micro-ROI gate verifies target stability, and speculative chained taps hit transient UI (e.g. auto-fading video controls) before they expire;
• Three-Layer Progressive Grounding Engine: Fuses local OCR with accessibility hierarchies (~150ms, 0 tokens) to drive 85%+ of standard actions via drift-free numeric indices, gracefully falling back to spatial vision models for custom Canvas/Compose/Flutter UI and sandboxed CV probing for subtle pixel states;
• Elastic Dual Engine with In-Flight Context Compactor: Seamlessly toggles between high-throughput reactive CI loops (Flash Mode, 3–5s/step) and multi-step cognitive state graphs (Pro Mode), using background visual deltas and DOM pruning to slash token consumption by >70% for 10+ hours of continuous, unattended soak testing.

Execution Profiles: Flash vs. Pro

ARTEMIS supports two execution profiles tailored for different automation requirements:

• Flash Profile (--profile flash): Fast and token-efficient reactive loop (~3–5s per step). Ideal for routine, deterministic UI tasks within 25–30 steps. Limitations: Does not support long-term state monitoring, video stream analysis, or multi-step failure self-healing.
• Pro Profile (--profile pro): Our most capable model architecture (~15–40s per step). Powered by a multi-agent graph with planning, visual verification, and automated recovery. Capable of handling 100+ step long-horizon workflows, continuous device state monitoring, and multimedia video analysis.

Roadmap

• Android Studio Integration: Native IDE plugin and workflow integration to enable in-editor debugging, test recording, and automated device control directly within Android Studio.
• iOS Platform Expansion: Extending multimodal perception and mobile automation to iOS devices and simulators.
• On-Device Lightweight VLMs: Local execution with lightweight edge vision models for low-latency, privacy-first automation.
• Real-time Duplex Voice Interaction: Voice-driven task dispatch with real-time conversational control and interruption handling.

Community & Contributing

Contributions are warmly welcomed!

• Star the repo to follow updates and releases
• Join the Discord Community for technical discussions
• Open an Issue or submit a Pull Request

License

This project is licensed under the Apache License 2.0.