BuildMCPServer
This project is a comprehensive guide on building a Model Context Protocol (MCP) server to deploy and manage a trained Random Forest model. It integrates with the Bee Framework to enhance interactivity and also provides methods for setting up a FastAPI hosted ML server.
What is the purpose of the MCP server?
The MCP server is designed to serve trained machine learning models and integrate them with frameworks like Bee Framework for enhanced interactivity, making it easier for developers to deploy and manage machine learning capabilities in their applications.
How do I set up the MCP server?
To set up the MCP server, clone the repository, set up a virtual environment, add the necessary packages, and run the server using the provided scripts.
Can I use the MCP server with other machine learning models?
Yes, the MCP server is designed to be flexible and can be used with various machine learning models, not just Random Forest.
Is the MCP server open-source?
Yes, the MCP server is open-source and licensed under the MIT License, allowing for community contributions and modifications.
Where can I find additional resources and tutorials?
Additional resources and tutorials can be found in the provided GitHub repositories and video links, which offer detailed instructions on building and deploying MCP servers.