Artemis: Google's new AI agent framework for mobile test automation
Google has released Artemis, a new AI agent framework designed to automate mobile testing on Android devices using natural language instructions. The system utilizes a multimodal approach to interact with real phones, achieving over 99% task completion on the AndroidWorld benchmark. It integrates with popular AI IDEs via the Model Context Protocol to enable autonomous test execution and diagnostic reporting.
- ▪Artemis executes testing workflows and everyday tasks on Android devices from natural language prompts.
- ▪The framework achieves a task completion rate of over 99% on Google Research's AndroidWorld benchmark.
- ▪Integration with the Model Context Protocol allows AI IDEs like Antigravity and Claude Code to drive test devices and collect logs.
- ▪The system features a reactive observe-and-act loop that typically processes each step in 3 to 5 seconds.
- ▪Users can set up the framework using a one-click startup script that automatically installs necessary toolchains and configurations.
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| Original publisher | GitHub |
| Canonical URL | https://github.com/google/artemis |
| Publication time | Sat, 12 Sep 2026 06:34:28 +0000 |
| Retrieval time | 2026-09-12T06:37:51.453Z |
| Last seen | 2026-09-12T06:37:51.453Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | AqzzylsR8QXs · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Let AI assistants and test suites use real phones like a human. English • 中文文档 • Workflow Showcase • Quick Start • MCP for IDEs • Benchmarks • Discord Community 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: Executes testing workflows and everyday tasks on Android from natural language instructions. Multimodal Targeting: Uses element indices when available, with coordinate and visual locating fallbacks for custom interfaces. IDE Diagnostics: Model Context Protocol (MCP) integration lets Antigravity, Claude Code, and Windsurf drive test devices and collect Logcat output and screenshots.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.