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

Enables MCP-compatible agents to publish marketplace services, poll and claim escrow-backed jobs, and submit fulfillments for review and payout.

MCP server for declarative intent execution. Agents submit intents — transfers, swaps, multi-hop routes — and the engine resolves and executes them atomically.

MCP server for AI agents to control a Mac via screen and mouse/keyboard, supporting Anthropic Claude and OpenAI for task automation.

An open-source MCP server that lets any coding agent operate your computer like a person does—reading the UI through accessibility trees, clicking and typing in the background, showing an agent pointer, zooming into regions, and driving your signed-in Chrome on macOS, Windows, and Linux.

Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables AI agents to use a desktop computer with event-driven settling, waiting for the screen to react and stabilize before returning a settled screenshot and verdict.

Enables MCP-speaking clients to control a real desktop via the computer_use tool, including clicking, typing, scrolling, dragging, key combos, app focus, and screen/accessibility capture. It also provides a verdict system that verifies whether input actions had their intended effect, with configurable approval modes.

Enables AI agents to drive a Linux/X11 desktop via AT-SPI accessibility-tree perception and element-level actions, avoiding screenshots and coordinate clicking.

Enables coding agents to ask what a window shows and receive a concise JSON answer from a local Ollama model instead of ingesting the full accessibility tree, reducing token usage. It is read-only and supports optional session context, health checks, and model release.

A self-hosted MCP server that enables AI agents to see and control a Windows PC through screenshots, built-in Arabic/English OCR, mouse, keyboard, clipboard, and application launching, with code-enforced consent and audit logging.

Enables an agent to see and operate a GNOME Wayland desktop like a human, including screenshots, mouse/keyboard control, accessibility tree access, OCR, clipboard, and audio listening.

MCP server enabling AI agents to control a real Linux browser with live view, human takeover, and safety guardrails.

This server enables AI agents to operate Windows and Linux computers by observing the screen, understanding the UI through accessibility, OCR, and vision, and performing mouse, keyboard, window, clipboard, and system actions with verification and recovery.

Open-source computer use MCP server for macOS and Windows, including remote Windows over SSH. Reads accessibility/UI Automation trees and uses Jev for element selection and action verification, with optional screenshot localization for icons and game scenes.

Enables agent-native desktop control by driving mouse, keyboard, and interface elements through accessibility-first semantic operations, with fallback to screen coordinates when accessibility cannot reach a target.

Enables MCP clients to inspect and control an Omarchy/Hyprland desktop by taking screenshots, focusing windows, moving/clicking the mouse, scrolling, typing text, and sending keyboard shortcuts.

Enables AI agents to operate local desktops and Chromium browsers through MCP tools, unifying accessibility trees, physical input, screenshots, DOM/ARIA, visual grounding, and result verification.

Enables AI hosts to drive cross-platform desktop GUI automation and browser control, providing tools to read, click, type, send shortcuts, screenshot, and verify GUI elements and web pages.

MCP stdio server that lets DSH agents see and operate Windows desktop apps via UI Automation, screenshots, mouse/keyboard, OCR, and window management.

Safety middleware for AI computer use agents that monitors, enforces policies, and provides guardrails to enable safe desktop interaction.

Gives each agent its own isolated nested Hyprland desktop with a private seat, clipboard and accessibility bus, so it can see the screen and drive a mouse, keyboard, touchpad gestures, windows and apps without touching the user's pointer, focus or windows. Exposes screenshots, zoom, OCR, accessibility-tree control, window management and batched actions as MCP tools, and can optionally act read-only, or with input, on the real desktop.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables MCP-capable AI agents to control Windows desktops through UI Automation element trees, native screenshots, app launching, batched action sequences, smart waits, and safety gates using normalized coordinates.

Enables localized macOS control by letting users grant temporary, window-scoped access for screen capture, pointer, keyboard, scrolling, clipboard, and Accessibility actions through a native host.

Enables LLMs to control Windows desktops via local OCR, optional YOLO icon detection, and mouse/keyboard actions.

Bridges Kimi Code CLI to OpenAI Computer Use, enabling Kimi to control local macOS applications via MCP.

Wraps OpenAI Codex's computer-use engine to provide MCP tools for Windows screen operations including screenshot, UI automation tree, and input simulation, enabling Claude Code to control the desktop.

Enables agents to discover and operate local macOS applications through ten Computer Use tools, including reading UI state and screenshots, clicking, typing, scrolling, and dragging, while requiring explicit human approval for new app access.

Enables agents to inspect and control macOS applications through Accessibility trees, screenshots, and OCR. It supports clicks, typing, key presses, scrolling, drags, clipboard paste, window actions, and scripted actions via MCP.