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. 33 tools, any MCP client.

Requirements

• macOS 15+
• iPhone connected via iPhone Mirroring

Install

/bin/bash -c "$(curl -fsSL https://mirroir.dev/get-mirroir.sh)"

or via npx:

npx -y mirroir-mcp install

or via Homebrew:

brew tap jfarcand/tap && brew install mirroir-mcp

The first time you take a screenshot, macOS will prompt for Screen Recording and Accessibility permissions. Grant both.

claude mcp add --transport stdio mirroir -- npx -y mirroir-mcp

{
  "servers": {
    "mirroir": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "mirroir-mcp"]
    }
  }
}

{
  "mcpServers": {
    "mirroir": {
      "command": "npx",
      "args": ["-y", "mirroir-mcp"]
    }
  }
}

codex mcp add mirroir -- npx -y mirroir-mcp

[mcp_servers.mirroir]
command = "npx"
args = ["-y", "mirroir-mcp"]

git clone https://github.com/jfarcand/mirroir-mcp.git
cd mirroir-mcp
./mirroir.sh

How it works

Every interaction follows the same loop: observe, reason, act. describe_screen gives the AI every text element with tap coordinates (eyes). The LLM decides what to do next (brain). tap, type_text, swipe execute the action (hands) — then it loops back to observe. No scripts, no coordinates, just intent.

Beyond the basics, the server exposes higher-level navigation and lifecycle tools: press_back navigates back by OCR-tapping the "<" chevron (with a canonical-position fallback), press_home/press_app_switcher/spotlight drive system gestures, scroll_to scrolls until a target text becomes visible, reset_app force-quits an app via the App Switcher, set_network toggles connectivity through Settings, and measure times how long an action takes to surface a target element. Multi-target setups use list_targets/switch_target to move between window automation endpoints.

... View full README on GitHub