Awesome MCP › Desktop Automation
The project "mcp-remote-macos-use" is an open-source MCP (Model Context Protocol) server designed to enable autonomous AI agents to fully control remote macOS systems. It integrates seamlessly with Claude Desktop, allowing AI to operate macOS environments without requiring additional API keys or software installations. This server acts as a direct alternative to OpenAI Operator, optimized specifically for autonomous AI agents with complete desktop capabilities. The project emphasizes a native macOS experience, leveraging the unmatched user experience of the macOS ecosystem, and aims to provide AI with fluent operation capabilities in this environment. Key features include no extra API costs by utilizing existing Claude Pro plans, minimal setup requiring only enabling Screen Sharing on the target Mac, and universal compatibility with all current and future macOS versions. The architecture supports universal LLM compatibility, allowing integration with any MCP client and flexibility to work with various LLM providers such as OpenAI and Anthropic. The design is future-proof to evolve with the MCP ecosystem. Deployment is effortless with zero setup on target machines, eliminating the need for background applications or agents on macOS. The server uses Screen Sharing for control, avoiding backend complexity common in other solutions. The user interface leverages Claude Desktop's polished UI, providing an intuitive and developer-friendly experience for interacting with AI-controlled Macs. The server supports WebRTC via LiveKit integration for low-latency real-time screen sharing, improved performance, and better network efficiency compared to traditional VNC. It offers a suite of tools for remote macOS control, including screen capture, keyboard input, mouse movements and clicks, application launching, and drag-and-drop operations, all configurable through environment variables. The project is actively maintained with a to-do list focusing on performance optimization, Apple Scripts generation, and VNC cursor visibility improvements. It supports Apple Authentication protocol 30 for secure connections. Overall, this project provides a powerful, open-source solution for autonomous AI control of macOS systems within the MCP framework, enhancing AI productivity and interaction with native macOS environments.
https://github.com/baryhuang/mcp-remote-macos-use
UI-TARS Desktop is a cross-platform GUI Agent application that uses a vision-language model to enable natural language control of computers with precise visual recognition and real-time feedback, integrating Model Context Protocol tools for advanced multimodal AI-driven automation.
Docker-Android packages Android emulators in Docker with VNC access, ADB control and log sharing for app testing, plus a beta MCP server image that exposes emulator control to AI agents.
Desktop Commander MCP is an MCP server for Claude that integrates AI with terminal control, file system search, and file editing capabilities, enabling advanced desktop automation and development workflows.
Windows-MCP is a lightweight, open-source MCP server that enables seamless integration and automation between AI agents using LLMs and the Windows operating system, supporting a wide range of UI interactions and system controls.
Peekaboo is a macOS-only MCP server and CLI tool that enables AI agents to capture and analyze screenshots with AI vision models for visual question answering and automation.
ios-simulator-mcp is an MCP server enabling AI-driven interaction, control, and inspection of iOS simulators for automated UI testing and quality assurance.
Terminator is an open-source automation tool for Windows that leverages the Model Context Protocol to enable AI-driven desktop and browser automation with high reliability and speed.
CodeRunner is an MCP server that securely executes AI-generated code locally on macOS using Apple's container technology, enabling private and efficient processing of local files with remote LLMs.