mirroir-mcp MCP Server
jfarcand/mirroir-mcp
[](https://agentrank-ai.com/tool/jfarcand--mirroir-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) MCP server for controlling a real iPhone via macOS iPhone Mirroring...and any MacOs app. Screenshot, tap, swipe, type — from any MCP client.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
jfarcand/mirroir-mcp is a Swift MCP server licensed under Apache-2.0. MCP server for controlling a real iPhone via macOS iPhone Mirroring...and any MacOs app. Screenshot, tap, swipe, type — from any MCP client. Topics: ai-agent, iphone, iphone-mirroring, macos, mcp, mcp-server, mobile-testing, model-context-protocol, real-device-testing, swift.
Ranked #731 out of 24846 indexed tools.
In the top 3% of all indexed tools.
Ecosystem
Score Breakdown
251 stars → growing community
Last commit 15d ago → recently updated
18/20 issues closed → responsive maintainer
4 contributors → small team
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
<p align="center"> </p> # mirroir-mcp Give your AI eyes, hands, and a real iPhone. An MCP server that lets any AI agent see the screen, tap what it needs, and figure the rest out — through macOS iPhone Mirroring. Experimental support for macOS windows. [38 tools](docs/tools.md), any MCP client. ## Vision: agents that test — and play mirroir is growing archetype-aware coverage for **games**. A game splits into two surfaces. The **shell** — menu, shop, loadout, settings, win/lose screens — is ordinary text-labelled UI that today's skills already drive. The **scene** — the playfield — is a vision-driven loop an agent follows one touch at a time. The honest targets are **game QA smoke tests, tutorial walkthroughs, and scripted demos**, not real-time play: iPhone Mirroring exposes a single pointer, so twin-stick and twitch games stay out of reach (see [Games](#games)). **Token reductions** make the scene loop affordable. Screenshots are ~90% of an agent's cost, so text-rich shell scRead full README on GitHub →
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