"Guide to Accessing and Managing my Mac Computer" 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.

A template MCP server that provides a basic structure and configuration for building Model Context Protocol servers. Includes Docker support, environment configuration, and examples for both STDIO and SSE transport modes.

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.

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.

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.

Enables weather lookups, mathematical calculations, and context-aware operations through a containerized MCP server with HTTP transport. Optimized for Docker/Kubernetes deployment with health checks and no external dependencies.

Enables AI assistants to run, manage, and debug BSD/Illumos VMs through natural language. Supports creating FreeBSD, OpenBSD, NetBSD, and OmniOS VMs, executing commands inside them, accessing console logs, and managing snapshots.

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

Run AI agents in VM-isolated sandboxes on your Mac.

Manages UTM virtual machines on macOS via AppleScript, enabling cloning, configuration, and control with unique MAC randomization.

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

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

Enables a computer-use agent to see and drive one isolated, sandboxed Linux desktop by exposing Anthropic's computer toolset actions alongside launching apps and listing windows, with screenshots scaled to a 1280-pixel longest side. It runs as a stdio MCP server scoped to a single screen and authenticated by an agent token.

A simple MCP server that allows accessing and executing shell commands on a VM machine through a web-based terminal interface, with automatic tunneling to make the VM accessible from anywhere.

Enables AI agents to create, drive, checkpoint, reset and delete resettable Windows and Ubuntu desktop VMs on Apple Silicon Macs, giving them real desktops to click, type and screenshot in plus shell commands, file transfer and port forwarding. All processing is local, so agents can work in isolated guests without leaving the Mac.

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 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 control Gazebo robot simulations through ROS2, including spawning robots (TurtleBot3), manipulating environments, accessing sensor data (camera, LiDAR, IMU), and managing simulation state.