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

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Python 3.12+ License: Apache-2.0 MCP Native Multi-Model AndroidWorld SOTA

Artemis in Action
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

Step 1: Prompt Input in Antigravity
2. Test Plan Generation
Formulates a step-by-step test plan & architecture for review

Step 2: Test Plan Generation
3. Autonomous Test Execution
Drives real device, navigates UI, and profiles performance

Step 3: Autonomous Test Execution
4. Comprehensive Final Report
Delivers structured audit findings, metric tables, and raw datasets

Step 4: Final Report
## 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 ```bash # 1. Clone repo & navigate to directory git clone https://github.com/google/artemis.git && cd artemis # 2. One-click launch ./start.sh ``` ### Windows PowerShell ```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): ```bash # 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 ` (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`): ```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`): ```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`): ```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`](./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`](./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**: Run `artemis mcp --install claude` to install the rules to `~/.claude/rules/artemis.md` (install to exactly one location — Claude Code loads both `~/.claude/CLAUDE.md` and `~/.claude/rules/*.md`, so duplicating the rules wastes context). * **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](./mcp_server/README.md). ### 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: ```python 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

Artemis Web Console
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](https://github.com/google-research/android_world) — 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.**

AndroidWorld Benchmark Comparison

## 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.

ARTEMIS System Architecture Diagram

## 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](https://discord.gg/wF2FN4WHGY) for technical discussions * Open an [Issue](https://github.com/google/artemis/issues) or submit a [Pull Request](https://github.com/google/artemis/pulls) ## License This project is licensed under the [Apache License 2.0](LICENSE).