"How to control a computer" matching MCP servers:

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Provides a persistent Docker computer with terminal, file editing, and optional desktop GUI control through a Three.js interface.

An MCP server that provides AI agents with a full Ubuntu desktop environment inside Docker, enabling them to perform complex computer tasks like browsing, coding, testing, and GUI automation.

Enables AI agents to control virtual computers through Orgo, supporting computer management, screen actions, shell commands, file operations, streaming, and AI completions.

Enables headless control of a DOSBox-X guest, including memory reading and patching, framebuffer capture, input injection, and live code tracing without interfering with the host desktop.

Enables an assistant to control a Tandy Color Computer 3 emulated in MAME, allowing typing, disk operations, screen viewing, and state management.

Enables MCP agents to automate real GUI applications on headless desktops, providing background mouse/keyboard control, window/process management, screenshots, and safe human handoff without disturbing the user's desktop.

Gives AI assistants full control over a VPS via SSH, enabling command execution, file management, service control, Docker and firewall management.

An MCP server for managing SearXNG instances, enabling configuration inspection, engine toggling, health checks, and container lifecycle control.

Enables AI agents to control real cloud phones by reading screens as text, tapping, typing, installing APKs, handing off to humans, and parking devices to stop billing, without ADB or emulators.

Enables AI assistants to manage Massed Compute GPU instances, including browsing inventory, launching and managing VMs, and auditing billing.

Provides AI agents with isolated virtual desktops containing a real Chromium browser, enabling them to see, click, type, and navigate like a human, with features like snapshots and remote control.

MCP server for building and driving VMware Workstation VMs from an AI agent, enabling unattended OS installs, guest command execution, file transfer, screenshots, and fleet management.

Enables an AI assistant to drive a Color Computer 3 emulated in MAME, including entering BASIC commands, mounting disk images, capturing screen snapshots, and peeking/poking memory.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

Enables AI agents to operate a real, private, local Docker-based computer with durable files, terminal access, web research, and a persistent browser or desktop. It supports multiple agent clients via MCP or OpenAPI, with live viewing and human takeover.

Provides native macOS desktop automation for AI agents, enabling screen capture, mouse/keyboard control, window management, and iOS/Android simulator control in both foreground and background modes without focus stealing.

A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.

An MCP server to control iOS Simulators.

Enables AI agents to manage VMware vSphere infrastructure through 55 typed tools built on the govc CLI. It supports comprehensive operations including VM lifecycle management, snapshot control, datastore navigation, and networking configuration.