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2025-04-07

AI Master Control Program (MCP) Server - Enabling AI models to interact with your system

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AI Master Control Program (MCP) Server

The AI MCP Server enables AI models, including locally hosted models with Ollama and Claude Desktop, to interact with your computer system. It acts as a bridge that allows AI models to:

  • Execute system commands
  • Create, read, update, and delete files
  • Control other programs
  • Communicate with each other

Architecture

The system consists of:

  1. MCP Server: Central server that processes requests from AI models
  2. Client Library: Enables easy integration with AI models
  3. Model Connectors: Interfaces with various AI model backends (Ollama, Claude Desktop, etc.)
  4. Task Execution Engine: Performs system operations and program control

Installation

Prerequisites

Automated Installation

For quick and easy installation, use the provided installation script:

# Clone the repository
git clone https://github.com/GrizzFuOnYou/master_mcp_server.git
cd master_mcp_server

# Run the installation script
python install.py

The installation script will:

  1. Verify Python version compatibility
  2. Install all dependencies
  3. Create a directory structure
  4. Configure environment variables
  5. Create platform-specific startup scripts
  6. Set up Claude Desktop as the default AI model

Manual Setup

If you prefer manual installation:

  1. Clone the repository:

    git clone https://github.com/GrizzFuOnYou/master_mcp_server.git
    cd master_mcp_server
    
  2. Install dependencies:

    pip install -r requirements.txt
    
  3. Configure environment variables:

    cp .env.example .env
    # Edit .env with your preferred settings
    

Usage

Starting the Server

Using Startup Script (Recommended)

After installation:

  • Windows: Run start_mcp_server.bat
  • Linux/Mac: Run ./start_mcp_server.sh

Manual Start

Run the MCP server:

python startup.py

By default, the server will listen on 0.0.0.0:8000.

Connecting AI Models

Claude Desktop (Default)

Claude Desktop is configured as the default model. To use it:

  1. Make sure Claude Desktop is running on your system
  2. The server will automatically attempt to connect on startup
  3. Claude Desktop should be available at the default location: http://localhost:5000/api

If you need to manually connect:

from mcp_client import MCPClient

# Initialize client
client = MCPClient("http://localhost:8000", "your-secret-api-key")

# Connect to Claude Desktop
result = client.connect_model("claude-desktop", "claude", {"api_url": "http://localhost:5000/api"})
print(f"Connection result: {result}")

Claude Desktop Connection JSON

If you need to manually configure Claude Desktop integration, use the following JSON configuration:

{
  "model_id": "claude-desktop",
  "model_type": "claude",
  "config": {
    "api_url": "http://localhost:5000/api",
    "temperature": 0.7,
    "max_tokens": 1000
  }
}

Ollama Models

To connect to an Ollama model:

from mcp_client import MCPClient

# Initialize client
client = MCPClient("http://localhost:8000", "your-secret-api-key")

# Connect to an Ollama model
result = client.connect_model("llama2", "ollama", {"host": "http://localhost:11434"})
print(f"Connection result: {result}")

Executing System Operations

Once connected, AI models can perform various system operations:

# Execute a command
result = client.execute_system_command("claude-desktop", "echo", ["Hello, World!"])

# Write a file
result = client.write_file("claude-desktop", "test.txt", "This is a test file created by Claude!")

# Read a file
result = client.read_file("claude-desktop", "test.txt")

# Start a program
result = client.start_program("claude-desktop", "notepad.exe")

# Stop a program
result = client.stop_program("claude-desktop", pid)

# Query the AI model
result = client.query_model("claude-desktop", "claude-desktop", "What is the capital of France?")

API Reference

Server Endpoints

Endpoint Method Description
/connect_model POST Connect to an AI model
/disconnect_model/{model_id} POST Disconnect from an AI model
/list_models GET List all connected models
/execute_task POST Execute a task requested by an AI model
/task_status/{task_id} GET Get the status of a task

Client Methods

Method Description
connect_model(model_id, model_type, config) Connect to an AI model
disconnect_model(model_id) Disconnect from an AI model
list_models() List all connected models
execute_system_command(model_id, command, args, working_dir, timeout) Execute a system command
execute_file_operation(model_id, operation, path, content) Execute a file operation
control_program(model_id, action, program_path, args, pid) Control a program
query_model(model_id, target_model, prompt) Query an AI model

Model Configuration

Claude Desktop Configuration

To connect to Claude Desktop, use the following configuration:

{
  "api_url": "http://localhost:5000/api",
  "temperature": 0.7,
  "max_tokens": 1000
}

Ollama Configuration

To connect to an Ollama model, use the following configuration:

{
  "host": "http://localhost:11434"
}

Security Considerations

IMPORTANT: This server grants AI models significant access to your system. Use with caution.

Security measures implemented:

  • API key authentication
  • Logging of all operations
  • Configurable permissions (coming soon)
  • Rate limiting (coming soon)

Troubleshooting

Claude Desktop Connection Issues

If you encounter issues connecting to Claude Desktop:

  1. Ensure Claude Desktop is running
  2. Verify the API URL (default: http://localhost:5000/api)
  3. Check the logs for specific error messages
  4. Restart Claude Desktop and try again

Ollama Connection Issues

If you encounter issues connecting to Ollama:

  1. Ensure Ollama is running (ollama serve)
  2. Verify the model exists (ollama list)
  3. Check the API URL (default: http://localhost:11434)
  4. Try pulling the model again (ollama pull modelname)

Extension Points

The MCP server can be extended to support:

  • Additional AI model backends
  • More sophisticated program control
  • GUI interaction capabilities
  • Web browsing capabilities
  • Network operation capabilities

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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    Reviews

    3 (1)
    Avatar
    user_u0VyN3qN
    2025-04-17

    I've been using master_mcp_server by GrizzFuOnYou, and it's simply outstanding. It provides seamless integration with my applications and the setup is remarkably intuitive. The detailed documentation on the GitHub link (https://github.com/GrizzFuOnYou/master_mcp_server) was very helpful, ensuring a smooth implementation. Truly a must-have for any MCP enthusiast!