Windows CLI MCP Server

What does “Windows CLI” MCP Server do?

The Windows CLI MCP Server is a Model Context Protocol (MCP) server designed to enable secure command-line interactions on Windows systems. It acts as a bridge between AI assistants and a system’s command-line interfaces (PowerShell, CMD, Git Bash) as well as remote systems via SSH. By exposing command execution, file access, and remote management as MCP resources and tools, it empowers AI-driven workflows to perform system tasks, automate operations, and interact programmatically with both local and remote environments. Its robust configuration and security options allow fine-grained control over what commands and directories are accessible, making it a powerful tool for developers who need to enhance their automation, scripting, and DevOps workflows while maintaining strong access controls.

List of Prompts

No prompt templates are explicitly mentioned in the repository documentation.

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List of Resources

• SSH Connections: Exposes a list of configured SSH connections as an MCP resource, allowing clients to view and select remote systems for command execution.
• Current Directory: Provides access to the current working directory as a resource, enabling context-aware operations.
• Configuration: Exposes server configuration details as an MCP resource, facilitating transparency and management of server behavior.

List of Tools

• Execute Local Shell Command: Allows execution of commands in PowerShell, CMD, or Git Bash on the local Windows system.
• Execute Remote SSH Command: Enables execution of shell commands on remote systems via SSH, using pre-configured connections.

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Use Cases of this MCP Server

• Local System Automation: Automate repetitive tasks on your Windows machine (e.g., file operations, system maintenance) via AI-driven command execution.
• Remote Server Management: Manage and interact with remote servers securely using SSH, ideal for DevOps and system administration tasks.
• Development Workflow Enhancement: Integrate with AI tools (like Claude Desktop) to streamline code compilation, testing, and deployment from the command line.
• Security-Conscious Operations: Enforce strict command and directory restrictions for safer automation in sensitive environments.
• Multi-Shell Interoperability: Seamlessly switch between PowerShell, CMD, and Git Bash within AI workflows for versatile script execution.

How to set it up

Windsurf

1. Ensure Node.js and npm are installed on your system.
2. Install the Windows CLI MCP Server package:

   npm install -g @simonb97/server-win-cli@latest
   

3. Locate your Windsurf configuration file (e.g., windsurf.json).
4. Add the MCP server using the following JSON snippet:

   {
     "mcpServers": {
       "win-cli": {
         "command": "npx",
         "args": ["@simonb97/server-win-cli@latest"]
       }
     }
   }
   

5. Save the file and restart Windsurf. Verify the server is running.

Securing API Keys

{
  "mcpServers": {
    "win-cli": {
      "command": "npx",
      "args": ["@simonb97/server-win-cli@latest"],
      "env": {
        "MY_SECRET_KEY": "${MY_SECRET_KEY_ENV}"
      },
      "inputs": {
        "apiKey": "${MY_SECRET_KEY_ENV}"
      }
    }
  }
}

Claude

1. Install Node.js and the server package globally or locally.
2. Open the Claude configuration file.
3. Add the server configuration:

   {
     "mcpServers": {
       "win-cli": {
         "command": "npx",
         "args": ["@simonb97/server-win-cli@latest"]
       }
     }
   }
   

4. Save changes and restart Claude.
5. Confirm connection to the Windows CLI MCP server.

Cursor

1. Install Node.js and the MCP server package.
2. Access the Cursor configuration file.
3. Insert the following into your configuration:

   {
     "mcpServers": {
       "win-cli": {
         "command": "npx",
         "args": ["@simonb97/server-win-cli@latest"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Verify integration by running a simple command.

Cline

1. Install Node.js and the MCP server.
2. Edit Cline’s configuration file.
3. Add the MCP server entry:

   {
     "mcpServers": {
       "win-cli": {
         "command": "npx",
         "args": ["@simonb97/server-win-cli@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Confirm the MCP server is active and responding.

Note: Always secure sensitive API keys or secrets via environment variables as shown above.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "win-cli": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “win-cli” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Roots support: Not mentioned in the documentation or code.

Based on the information above, the Windows CLI MCP Server offers strong utility for developers needing secure, AI-driven command-line access and remote automation. It covers most MCP primitives except for prompt templates and explicit sampling/roots support. Its documentation is clear and practical.

Our opinion

I would rate this MCP server a solid 8/10. It is robust, well-documented, and practical for real-world use cases, but lacks some advanced MCP features (like prompt templates and sampling/roots support) that would make it even more versatile.

MCP Score