"How to operate a computer and execute commands" matching MCP servers:

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.

Gives a coding agent its own Docker-hosted Linux desktop with XFCE, Chromium, Blender, LibreOffice, GIMP and a sudo shell, exposing tools for screenshots, mouse and keyboard input, window focus, shell commands, file read/write, opening URLs or GUI apps, and headless Blender renders. The agent can watch and drive that desktop live from a browser while working on the shared project folder.

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.

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

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.

Cloud Linux desktops for AI agents. Create a computer, see its screen through screenshots, and drive it with click, type, drag and keys, or hand off a whole task with run_agent. Also hosted with OAuth at https://app.mandala.computer/mcp.

Enables AI coding agents to perform automated Blender UI testing, user-story validation, and computer-use workflows inside an isolated GPU-partitioned Windows 11 VM without disrupting the host desktop.

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

Universal Docker MCP server for AI assistants (Cursor, Claude Desktop). Manage Docker containers, execute commands, query databases, and handle environment configurations — all through natural language.

Enables MCP clients to inspect and operate Kubernetes clusters across multiple contexts, with read-only/read-write/admin access modes and security flags controlling namespaces, contexts, deletes, applies, and exec.

An OpenAPI-driven MCP server for Proxmox VE that provides 2 generic tools to execute any of 480+ API operations dynamically, plus tools for executing commands inside VMs and containers, saving ~95% tokens.

Let your AI build and run a whole app on your computer: an online shop, website, booking app or AI helper. It creates the parts, starts them, checks they work and fixes problems.

An MCP server that exposes Runloop Devbox operations as tools, enabling AI agents to create and manage Linux sandboxes, execute commands, edit files, snapshot disks, and drive interactive PTY sessions.

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

Enables AI agents to explore and operate OpenShift/Kubernetes clusters, offering read-only tools for projects, pods, logs, and resources, with opt-in higher modes for scaling, restarts, applying manifests, and deletions under safe-by-default guards.

A private MCP server that lets ChatGPT create, manage, and operate Box by ASCII Linux environments through secure MCP tools.

MCP server for managing Proxmox VE clusters — provision VMs and containers, manage snapshots and backups, execute commands, browse storage, and monitor resources through natural language

Enables MCP-capable clients to inventory and operate Azure resources via the Azure Resource Manager API, including resource groups, tags, and VM power, while enforcing governance controls like scoping, protected groups, location allowlists, delete gating, and confirmation.

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

Enables management of Sprite VMs through interactive dashboards and terminal interfaces. It allows users to execute commands, create filesystem snapshots, transfer files, and manage VM lifecycles via natural language.

Enables AI assistants to manage Docker containers, execute commands inside them, and inspect container information through a minimalist set of tools supporting both stdio and HTTP transports.

A Model Context Protocol server that enables AI clients to interact with virtual Ubuntu desktops, allowing them to browse the web, run code, and control instances through mouse/keyboard actions and bash commands.

Nido is a local QEMU VM manager. Install it on your computer from https://github.com/Josepavese/nido and run nido mcp via stdio, or use npx -y nido-mcp@latest mcp with QEMU installed locally. It manages VMs on that same computer; a server hosted by Glama cannot access your local VM inventory.

Provides tools for managing vcluster instances, enabling AI assistants to list, describe, create, delete, pause, resume, and execute commands inside virtual clusters.

An MCP server that enables interaction with development containers through the devcontainers CLI, allowing users to start, run commands in, and execute arbitrary shell commands inside devcontainers.

Enables MCP-capable agents to control a real QEMU virtual machine through nine computer-use tools—screenshot, click, move, type, key, scroll, status, start, and stop—without accessing the host’s pointer, clipboard, or files.

Enables AI coding agents to work inside a disposable Windows guest desktop, where they can run shell commands, launch applications, inspect and operate native GUI controls, perform browser DOM actions, and transfer files. Fresh observations, PNG screenshots, and hashed artifacts let agents verify results without touching the host desktop.