"Exploring Computer Usage" 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.

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

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.

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

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.

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

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 multiplayer first-person 3D virtual house environment with interactive elements including a TV with image display system and computer terminal for accessing MCP systems.

Governed XCP-ng operations via Xen Orchestra REST — VM-health, SR-usage, backup-failure, and patch-state RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

MCP server for securely discovering, pricing, renting, connecting, and releasing GPU compute instances from AI Galaxy with budget checks and two-phase approval.

A Model Context Protocol server for managing cloud servers, particularly DigitalOcean droplets, allowing users to identify providers via IP addresses and perform operations like power management, status monitoring, and resource usage tracking.

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.

Transforms idle LAN machines into a unified compute cluster for AI agents to offload CPU-intensive tasks like simulations and backtesting. It provides a broker-worker architecture that integrates with MCP-compatible tools to distribute workloads across a local network.

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.

Enables AI assistants to manage Google Cloud Batch HPC jobs and Compute Engine VMs through conversational prompts, including submitting jobs, provisioning instances, and retrieving diagnostics.

Enables autonomous desktop automation by delegating tasks to vision-based agents operating within cloud-based virtual machine sandboxes. It allows users to manage VMs, execute complex computer tasks, and receive text-based screen summaries across Linux, Windows, and macOS environments.