# Drengr

> AI-native mobile testing. No selectors, no XPath, no flaky locators.

Drengr is an MCP server that gives AI agents eyes and hands on mobile
devices. It connects to Android, iOS, and cloud device farms, exposing
3 tools: drengr_look (observe), drengr_do (act), drengr_query (query).

## Docs

- [Website](https://drengr.dev)
- [Install](https://drengr.dev): `npm install -g drengr`

## Tools

- drengr_look: Observe the device screen (annotated image or ~300-token text)
- drengr_do: Execute actions (tap, type, swipe, long_press, back, home, launch, wait, key, install, clear_and_type, scroll_to_top, scroll_to_bottom) with automatic situation reports
- drengr_query: Query device state (connect, devices, activity, crash, find, explore, session, network, logcat, keyboard, app_state, assert, diff, ui_dump, analyze)

## Platforms

- Android via ADB (physical devices and emulators)
- iOS via simctl (booted simulators on macOS)
- Cloud: BrowserStack, SauceLabs, AWS Device Farm, LambdaTest, Perfecto, Kobiton, any Appium hub

## LLM Providers

Gemini (default), OpenAI, Anthropic, Groq, Together, Fireworks, Ollama (local/offline)

## Install

```
npm install -g drengr
curl -fsSL https://drengr.dev/install.sh | bash
```

## CLI

```
drengr mcp        Start MCP server (stdio)
drengr devices     List connected devices
drengr run         Run AI agent task on device
drengr test        Run YAML test suite
drengr explore     BFS app screen mapping
drengr setup       Generate MCP config for Claude/Cursor/Windsurf/VS Code
drengr doctor      Check system health
```

## Key Capabilities

- Text-only mode: ~300 tokens per screen (100x cheaper than vision)
- Vision escalation: auto-switches to screenshots when elements lack labels
- Situation reports: structured diffs after every action (new/disappeared elements, navigation, crash, stuck detection)
- Screen maps: BFS exploration builds navigation graphs cached at ~/.drengr/maps/
- Network capture: HTTP calls from device logs returned in action responses
- In-app SDK: optional OkHttp (Android) / URLSession (iOS) interceptors for richer capture
- YAML test suites: natural language tasks with JUnit XML output for CI

## Optional

- [llms-full.txt](https://drengr.dev/llms-full.txt): Extended documentation with full architecture details