Automation MCP

Automation MCP – Desktop Automation for AI Assistants

Automation MCP is a Model Context Protocol server that grants AI models full control over macOS desktops. By exposing low‑level input and screen manipulation primitives, it turns an AI assistant into a powerful remote operator capable of interacting with any application as if a human were using the keyboard and mouse. This solves the long‑standing problem of AI assistants being confined to text or API calls, enabling them to perform tasks that require visual perception and direct user‑interface manipulation.

The server offers a rich set of tools grouped around three core capabilities: input simulation, screen capture & analysis, and window management. Input tools let the model click, drag, type text, or execute system shortcuts; screen tools allow capturing full‑screen or region screenshots, querying pixel colors, and waiting for specific images to appear; window tools provide the ability to enumerate open windows, focus or move them, and resize or minimize. These primitives are deliberately simple yet expressive enough that higher‑level workflows—such as filling out forms, navigating menus, or automating repetitive UI tasks—can be composed without writing custom code.

For developers, Automation MCP is valuable because it integrates seamlessly into existing MCP‑based workflows. Once the server is running, any Claude or other MCP‑compatible client can invoke its tools by name and pass arguments in the standard JSON format. This makes it trivial to extend an AI assistant’s capabilities: a user can ask the model to “open Safari, search for the latest Apple news, and take a screenshot of the top article” and receive an image back—all through natural language. The server’s design also respects macOS security by requiring only the Accessibility and Screen Recording permissions, keeping the user in control of what the assistant can do.

Real‑world use cases abound. In quality assurance, an AI could launch a web app, navigate the UI, and verify visual elements by comparing screenshots. In accessibility support, the assistant could translate spoken commands into mouse movements and keystrokes for users with limited mobility. In workflow automation, repetitive tasks such as data entry, file organization, or system configuration can be scripted through the MCP interface and triggered by simple prompts.

Unique to Automation MCP is its focus on macOS desktop environments, leveraging native APIs for accurate input simulation and visual analysis. The inclusion of image‑matching tools like allows the model to pause until a particular UI element appears, adding robustness to dynamic interfaces. Together, these features make Automation MCP a powerful bridge between conversational AI and the full breadth of desktop interaction.