Windows CLI MCP Server

Overview

The Delorenj Super Win CLI MCP Server is a hardened, high‑privilege fork of the original Windows CLI MCP Server. It removes all application‑level restrictions and grants an AI assistant complete control over a Windows host, while still enforcing network‑level isolation. This makes it ideal for scenarios where an AI needs to perform arbitrary system administration, automation, or troubleshooting tasks without the overhead of sandboxing each command.

By installing itself as a Windows service with SYSTEM privileges, the server can execute any shell (PowerShell, CMD, Git Bash) or native binary, read and write anywhere on the file system, and spawn long‑running processes. The server also supports unlimited process resources, extended timeouts, and automatic recovery of the service after failures. These capabilities let developers build robust workflows where an AI can, for example, compile code, run tests, manage services, or modify system configurations in a single turn.

Key features include:

• Full shell access – any command or script can be launched through PowerShell, CMD, or Git Bash without argument filtering.
• Unrestricted file system – read/write/execute permissions across the entire drive, enabling AI‑driven file manipulation or data extraction.
• SYSTEM‑level service installation – the server itself runs as a privileged Windows service, ensuring persistence and high availability.
• Network‑level controls – the server binds to localhost by default, but administrators can whitelist IP ranges or require VPN connections for added security.
• Process reuse and fault tolerance – existing processes are reused where possible, and the service automatically restarts if it crashes.

Typical use cases involve advanced DevOps automation, security testing, or remote maintenance. For instance, an AI could receive a high‑level instruction like “Deploy the latest build to the production server,” and the MCP would compile, transfer, and restart services with full system access. In a trusted lab environment, the server allows AI assistants to explore and manipulate the host as if they were a human operator, dramatically speeding up debugging, configuration management, or data‑collection tasks.