windows-user-space-emulator/mcp/README.md

Sogen MCP Server

A Model Context Protocol (MCP) server that provides AI access to the sogen userspace emulator.

Setup

1. Install dependencies:

   npm install
   

2. Run the server:

   npm start
   

   Or for development with auto-restart:

   npm run dev
   

Structure

• server.js - Main server implementation
• package.json - Node.js project configuration

Available Tools

list_applications

Lists all available applications in the sogen userspace emulator.

Parameters: None

Example usage:

{
  "name": "list_applications",
  "arguments": {}
}

run_application

Executes a specific application from the allowed list in the sogen userspace emulator.

Parameters:

• application (string, required): The name of the application to run (use list_applications to see available apps)
• args (array of strings, optional): Arguments to pass to the application
• timeout (number, optional): Timeout in milliseconds (default: 5000)

Example usage:

{
  "name": "run_application",
  "arguments": {
    "application": "echo",
    "args": ["Hello from sogen!"],
    "timeout": 3000
  }
}

Adding More Tools

To add additional tools:

1. Add the tool definition to the ListToolsRequestSchema handler
2. Add the implementation to the CallToolRequestSchema handler
3. Create the corresponding method in the MyMCPServer class

Execution Model

The server uses an analyzer-based execution model:

• Applications are not executed directly
• Instead, the server runs: C:/analyer.exe -e C:/somedir <application_name> [args...]
• The analyzer handles the actual execution within the sogen environment
• All output comes from the analyzer process

Command Structure

C:/analyer.exe -e C:/somedir <application_name> [arguments...]

Where:

• C:/analyer.exe - The sogen analyzer executable
• -e C:/somedir - Analyzer flags and environment directory
• <application_name> - The application from get_applications()
• [arguments...] - Optional arguments passed to the application

Implementation Required

You need to provide the implementation for the get_applications() method in server.js. This method should:

async get_applications() {
  // Return a Promise that resolves to a string array
  // Example: return ['echo', 'ls', 'cat', 'grep'];
}

Usage

This server allows AI assistants to:

1. List available applications using list_applications
2. Execute specific applications using run_application with validation

The server communicates over stdio and is designed for MCP-compatible clients.

Example Workflow

1. Call list_applications to see what's available
2. Call run_application with a valid application name and arguments

Next Steps

1. Implement get_applications() method - Provide the actual implementation
2. Add application-specific argument validation
3. Implement resource handling for file access
4. Add comprehensive logging and monitoring
5. Consider per-application sandboxing for enhanced security