AI Master Control Program (MCP) Server
by GrizzFuOnYou
The AI MCP Server enables AI models to interact with your computer system, acting as a bridge for executing commands, managing files, controlling programs, and communicating with each other. It supports locally hosted models like Ollama and Claude Desktop.
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What is AI Master Control Program (MCP) Server?
The AI MCP Server is a central server that allows AI models to interact with your computer system. It provides a client library and model connectors to interface with various AI model backends, enabling tasks like executing system commands, managing files, and controlling programs.
How to use AI Master Control Program (MCP) Server?
First, install the server using the automated script or manual setup. Then, start the server using the provided startup scripts or manually via python startup.py. Connect AI models like Claude Desktop or Ollama using the client library and the connect_model method. Finally, use the client library to execute system operations, file operations, or control programs.
Key features of AI Master Control Program (MCP) Server
Centralized server for AI model interaction
Client library for easy integration
Support for multiple AI model backends (Ollama, Claude Desktop)
Ability to execute system commands
File management capabilities (create, read, update, delete)
Program control (start, stop)
API key authentication
Use cases of AI Master Control Program (MCP) Server
Automating system tasks with AI models
Creating AI-powered assistants with system control
Integrating AI models with existing applications
Building AI-driven automation workflows
FAQ from AI Master Control Program (MCP) Server
What AI models are supported?
What AI models are supported?
Currently, the server supports Claude Desktop and Ollama models. Support for additional models can be added through extensions.
How do I connect to Claude Desktop?
How do I connect to Claude Desktop?
Ensure Claude Desktop is running and use the provided configuration with the connect_model method, specifying the API URL (default: http://localhost:5000/api).
How do I connect to Ollama?
How do I connect to Ollama?
Ensure Ollama is running and use the provided configuration with the connect_model method, specifying the host (default: http://localhost:11434).
What security measures are in place?
What security measures are in place?
The server implements API key authentication and logging of all operations. Configurable permissions and rate limiting are planned for future releases.
How can I contribute to the project?
How can I contribute to the project?
Contributions are welcome! Please feel free to submit a Pull Request.