Automates real iOS device interactions using AI-driven screen recognition and intent-based automation flows.
The Mirroir Skills library provides a collection of community-contributed automation scenarios for real iPhone hardware via the Mirroir MCP server. Unlike traditional brittle scripts that rely on static coordinates, these skills use natural language 'intents' and OCR-based screen analysis to navigate apps, handle dynamic layouts, and execute complex workflows. This skill is essential for developers and QA engineers looking to perform end-to-end testing or automate repetitive tasks on physical iOS devices using Claude's reasoning capabilities.
Key Features
01Extensive library of pre-made flows for popular iOS applications
02Dynamic element detection via describe_screen OCR and vision analysis
031 GitHub stars
04Complex logic support including conditional branching and loops
05Automatic compilation for deterministic, high-speed replay
06Intent-based iOS automation using natural language descriptions
Use Cases
01Streamlining repetitive mobile workflows like messaging or data entry
02Automated end-to-end (E2E) testing on physical iPhone hardware
03Building AI agents capable of interacting with the full iOS ecosystem
