"How to connect WSL to Windows" matching MCP servers:

Read-only observability MCP for Windows, WSL, Docker, and WSLC.

Lets AI agents manage local virtual machines: create macOS and Linux VMs on Apple silicon and WSL distros on Windows, start/stop, clone, back up, and run commands inside them.

Enables AI agents to manage WSL containers and images via the wslc CLI, supporting container lifecycle, network, volume, and registry operations through natural language.

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.

Connect any MCP-compatible AI agent to the full Hostinger platform. Manage VPS, domains, DNS, hosting, WordPress, email, ecommerce, and more through natural language.

MCP server that discovers Korean e-Government and financial websites and launches them in a clean disposable Windows Sandbox (or macOS macSandbox) without requiring security software installation. It handles search and sandbox execution, leaving authentication and actual tasks to the user.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

Enables LLMs to remotely control VirtualBox VMs and Playwright browsers on Windows, including VM lifecycle actions, in-guest commands, browser automation, window management, and service monitoring via REST API and MCP.

Enables agent clients to safely connect to tools and execution resources through MCP with authorization, approvals, audit, chat-context isolation, SSH/Docker access, and long-running command session tracking.

An MCP server that gives an LLM full control over a VMware-hosted Windows VM: lifecycle, snapshots, remote execution, file transfer, and kernel debugging.

Enables AI clients to control VMware Workstation virtual machines by viewing the console, operating the mouse and keyboard, running guest commands, and managing power and snapshots across multiple named Windows and Linux VMs.

Enables AI agents to manage virtualization, Active Directory, Windows hosts via WinRM, PostgreSQL databases, and shell/SSH environments through Model Context Protocol tools.

Enables AI agents to dynamically spawn, route to, and manage ephemeral containerized sandboxes on Kubernetes without requiring Custom Resource Definitions or cluster-level operators.

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.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

An MCP server that gives LLM agents full API access to a VMware Cloud Foundation 9.1 estate, exposing 8,931 operations through eight tools with automatic authentication, async task tracking, and write safety.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.

Enables LLM agents to control NVIDIA Run:AI infrastructure by dynamically searching and executing over 426 Run:AI APIs through MCP tools.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.