"How to open desktop applications on Windows" matching MCP servers:

An MCP server that lets agents observe and control an Omarchy or Hyprland desktop: list monitors, windows, workspaces, and accessibility controls, capture screenshots, then move the pointer, type text, send shortcuts, and manage windows and workspaces. It works over stdio with any MCP client, guarding actions with session-lock and single-driver checks while treating on-screen content as untrusted data.

A compact facade MCP server for macOS desktop automation, lazily proxying to full-featured computer-use tools to save context tokens while enabling screenshots, window control, app launching, and AppleScript execution.

Enables AI agents to capture multi-monitor screenshots with coordinate grids and perform mouse, keyboard, scrolling, dragging, and window-management actions on Windows via MCP tools or CLI. It provides pixel-accurate desktop automation for computer-use agents.

Exposes a Windows GUI agent as MCP tools so any MCP client can drive the real desktop through natural language: clicking, typing, scrolling, launching apps and running PowerShell, with fallback LLM providers for resilience. Also offers read-only inspection of open windows, the UI Automation tree and multi-monitor screenshots without invoking an LLM.

Enables supervised, visible control of a Windows desktop from an MCP client, providing real mouse and keyboard input, screenshots, local safety controls, and a teaching mode for guidance without injection.

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

Enables multiple local AI desktop applications to exchange MCP messages and collaborate through a shared JSONL room file, with role-based routing, history, and audit session tools.

Enables MCP clients to capture screenshots and control a Raspberry Pi's Wayland desktop over an existing SSH connection with mouse, drag, scroll, keyboard, and Unicode typing actions. Input tools return fresh screenshots, enforce single-client sessions with idle release, and reject stale or uncertain state until verified.

A Windows-only MCP server that gives AI models eyes and hands on a Windows machine, enabling file reading, screenshots, mouse/keyboard injection, and an auto-debug loop with a safety-focused watchdog for protected abort regions.

Enables a local MCP client to drive an already-open DeepSeek Harness Desktop session over a loopback-only, Bearer-authenticated endpoint — submitting standard-mode tasks, reading bounded output, continuing or canceling runs, and inspecting diagnostics.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables asynchronous two-way messaging between Codex Desktop tasks and Claude Desktop Code sessions on Windows, allowing either side to share information, questions, or updates through MCP tools.

Enables Claude Code, Cursor, and Codex users to orchestrate plan/build/review workflows across host or CLI models with a spec gate, tool vetting, hard per-run and per-day cost/token limits, safe defaults, and clear logs.

Enables guarded, local-first perception and interaction with Windows desktops through UI Automation, screenshots, and bounded mouse/keyboard actions with deterministic verification. It prioritizes semantic/read-only inspection and excludes arbitrary shell execution or destructive system operations.

Enables agents to control Windows desktop applications through UI Automation and Win32, supporting window management, mouse/keyboard input, element inspection, screenshots, OCR, macro recording, and autonomous multi-app missions. It also provides an HTTP/stdio MCP interface, an operator UI, and optional telemetry and safety controls.

Enables MCP clients to observe Windows accessibility trees and deltas, generate fail-closed semantic action plans for external authorized executors, and control isolated, agent-owned Chrome tabs without accessing personal tabs.

Enables durable bidirectional handoffs between any MCP client and OpenAI Codex Desktop tasks, with persistent callbacks, acknowledgements, and session-scoped state across restarts.

Enables AI models to control a local Windows desktop by moving the cursor, clicking, scrolling, typing Unicode text, sending key chords, and capturing screenshots. Runs natively on Windows with minimal latency and no heavy dependencies such as Python, PyAutoGUI, or Docker.

Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.

MCP server for Windows desktop automation, enabling agents to control mouse, keyboard, and UI elements via 22 tools, with OCR, screenshots, macro recording, and autonomous mission execution.