"A platform for designing and prototyping user interfaces and experiences" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Windows桌面截图与窗口自动化工具，支持后台操作、不抢焦点，可截取窗口/屏幕、模拟鼠标键盘、点击菜单等。

A small MCP server that wraps MoneyMoney on macOS via AppleScript, exporting account lists and transactions (bookingDate, amount, name, purpose) as plists for invoice reconciliation, complementing a companion Apple Mail server.

Enables an AI agent to operate a spare Android phone through MCP: capture screenshots, inspect UI controls, tap/swipe, input Chinese text, launch apps, and optionally run rooted shell commands or transfer files. It also supports a live web console for remote viewing and control.

A modern, extensible server that provides a unified interface to control and interact with various macOS applications through plugins.

Enables any AI agent to perceive and control a Windows desktop through live screen capture, OCR, and safety-gated mouse/keyboard actions via a local HTTP API and MCP.

An MCP server that enables secure terminal command execution, directory navigation, and file system operations through a standardized interface for LLMs.

Enables AI agents to manage processes via structured MCP tools, reducing token usage by 75-80% compared to shell commands.

A server that enables programmatic interaction with an already running Abaqus/CAE GUI application, allowing users to execute Python scripts and retrieve message logs through the Model Context Protocol (MCP).

Enables MCP clients to discover desktop applications with structured metadata and receive native accessibility trees and screenshot content through Open Computer Use, preserving upstream tool results and image blocks.

Enables AI agents to manage Supervisord processes (start, stop, restart, view logs, etc.) through the Model Context Protocol, simplifying process management in production and development environments.

Enables Claude to see and interact with any macOS application using natural language commands. Perfect for testing Mac applications, UI automation, and app development with AI assistance.

An MCP server that provides weather alerts and forecasts, system shutdown/restart, smart browser search, and screenshot capture.

Node.js server implementing Model Context Protocol that enables seamless interaction between Windows and Linux distributions under WSL, allowing file operations like reading, writing, searching, and managing files across the WSL filesystem from Windows.

Sends periodic system notifications to remind users to take breaks and move around, with customizable intervals, messages, and cross-platform notification support.

Enables Claude Code to read and operate macOS app interfaces through the accessibility tree, pressing buttons, setting text fields, typing with IME support, sending shortcuts, scrolling, dragging, and capturing screenshots. It drives background apps without moving the mouse or stealing focus from the user's current work.

Gives AI assistants local access to a Mac's clipboard history, letting them search past clips and lists, read a clip in full (including text recognized inside screenshots), and place a clip back on the system clipboard for the user to paste. Everything runs over 127.0.0.1 with explicit user approval, and assistants cannot delete clips or see items concealed by password managers.

An MCP server that connects AI assistants to the NinjaOne remote monitoring and management platform via the REST API v2. It provides tools for device inventory, organization management, alert handling, maintenance scheduling, and automated job execution.

Enables AI agents to automate GUI interactions across Windows, Linux, macOS, Android, iOS, and browsers using structured platform APIs first, with vision grounding as a fallback for robust cross-platform computer use.