# Machine learning

Summary of the MCP-DeanMachines project

A server project compatible with the MCP protocol, providing atomic-scale simulation functions through ASE, pymatgen, and machine learning interatomic potentials (MLIPs). It is currently under active development.

The OpenML MCP Server is a tool that provides access to the OpenML API through the MCP protocol, allowing users to directly query machine learning resources such as datasets, tasks, and processes from MCP-compatible clients (such as Claude Desktop).

This project provides a complete guide for building an MCP server, which is used to deploy trained random forest models and integrate with the Bee framework to implement ReAct interaction functions.

The Cloudera ML Model Control Protocol (MCP) is a Python toolkit that provides functions for integrating with the Cloudera Machine Learning platform, including services such as file management, job scheduling, model management, and experiment tracking.