"How to operate a computer" matching MCP servers:

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.

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.

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.

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

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

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.

Enables AI agents to inspect and operate a Kubernetes cluster safely, with read-only mode and namespace allowlist for mutations.

Enables AI agents to inspect and operate multiple Kubernetes clusters through natural language, providing multi-cluster diagnostics, RBAC analysis, security checks, and app-centric deployment with GitOps and smart workload placement.

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

Enables AI agents to operate disposable Linux computers via MCP, providing tools for shell, file read/write, directory listing, and port exposure. It also supports browser automation and integration with any MCP-compatible client.

Enables assistants to operate a home lab through one authenticated HTTPS endpoint, including managing Proxmox VMs and containers, Home Assistant and ESPHome devices, Docker, shell access over SSH, Fully Kiosk tablets, and network discovery.

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.

An MCP server that lets AI assistants safely inspect and operate on Kubernetes clusters through natural conversation.

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.

Enables AI agents (like Claude Code, Cursor) to directly operate Unity scenes via MCP protocol, with tools for scene hierarchy, object creation/deletion, and transform modification.

Enables AI agents to dynamically spawn, route to, and manage ephemeral containerized sandboxes on Kubernetes without requiring Custom Resource Definitions or cluster-level operators.