"A powerful filesystem that works on both Windows and Mac" matching MCP servers:

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

A lightweight server that enables AI agents to interact natively with the Windows operating system for tasks like UI automation and application control. It allows LLMs to perform file navigation, simulate user input, and manage windows without requiring specialized computer vision models.

Provides advanced filesystem operations for AI-assisted development, including batch file reading, renaming, moving, project structure display, and command execution with Python virtual environment auto-activation.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

Enables MCP-compatible coding agents to schedule, check, postpone, and cancel Windows host shutdowns from WSL.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Local macOS MCP bridge that gives ChatGPT shell, unrestricted filesystem access, real PTY sessions, background jobs, and read-only stored Codex history. ChatGPT stays the reasoning layer; the bridge makes no model calls.

Enables ChatGPT on the web or mobile to run commands and edit files on a Windows PC through OpenAI Secure MCP Tunnel without opening inbound ports or exposing a public address.

A lightweight Windows automation MCP server that scopes UI operations to a single target window, offering tools like ReadWindow, PeekWindow, Click, Type, Scroll, Screenshot, and App management with reduced token usage compared to full-desktop alternatives.

Enables MCP clients such as ChatGPT to execute shell commands, manage files, and view or capture images on Mac and Linux hosts. Supports terminal-based connection approval, time-limited access, and output controls.

Enables batched filesystem operations on allowed directories and standalone Windows shell command execution, including background jobs and interactive console windows, through MCP tools.

Self-learning macOS automation MCP server that remembers successful patterns and avoids repeated failures, enabling AI agents to execute multi-step workflows via reusable recipes.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

Enables launching and controlling real, visible Windows Telnet windows by reading their screen buffers and sending keyboard events, with session management and text-waiting capabilities.

Enables voice-controlled hardware to execute approved Mac actions (like opening apps and querying system status) through a secure MCP bridge.

An MCP server that allows secure execution of macOS terminal commands through Claude or Roo Code with built-in security whitelisting and approval mechanisms.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Enables AI coding agents to work inside a disposable Windows guest desktop, where they can run shell commands, launch applications, inspect and operate native GUI controls, perform browser DOM actions, and transfer files. Fresh observations, PNG screenshots, and hashed artifacts let agents verify results without touching the host desktop.

Provides comprehensive Windows system control including file operations, process management, window control, screenshots, clipboard access, PowerShell/CMD execution, and optional mouse/keyboard automation and browser control capabilities.

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.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables AI assistants to find and launch Windows applications by name using multi-strategy discovery via registry, Start Menu, PATH, and common directories.

Enables Claude to fully control a Windows desktop with native screen capture, low-level input injection, game-grade input, and play-testing capabilities.

Enables ChatGPT to safely interact with Windows workspaces through a loopback-only MCP server, with OAuth, bounded PowerShell tools, persistent jobs, and optional Cloudflare Tunnel exposure.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables agents to manage and operate macOS VM workspaces through authenticated MCP tools, including lifecycle control, command execution, job monitoring, and access to desktop connection and guest login details.

Self-hosted server that lets ChatGPT, Grok, and stdio MCP clients read and write files, run PowerShell/CMD and interactive processes, and drive the Windows desktop through screenshots, window info, clicks, drags, and keyboard input. It connects via OpenAI Secure MCP Tunnels, an OAuth authorization-code + S256 PKCE HTTPS endpoint, or local stdio, exposing 38 tools under the user's own Windows account.

Enables secure remote development on Windows by allowing LLM clients to manage files, run commands, and automate browsers within sandboxed workspaces, with multi-project switching and OAuth authentication.

Enables secure command-line interactions on Windows systems with support for PowerShell, CMD, Git Bash, and WSL shells, providing controlled file access, command execution, and configurable security restrictions.