This project develops an open-source computational platform to study the magnetic and electronic properties of strongly correlated materials (SCMs), which are essential for emerging technologies and devices related to quantum computing, spintronics, and magnetic storage. SCMs exhibit complex behaviors that are difficult to capture through conventional static theories or based on pure experimental measurements. By incorporating dynamical fluctuation effects into conventional first-principles methods, this project offers a new way to accurately simulate magnetic phenomena at multiple scales, from atomic spins to macroscopic magnetism. The developed software automates the modeling workflow and enables users to compute critical properties such as magnetic ground states, exchange interactions, spin excitations, and temperature-dependent magnetic transitions. By integrating this tool with community-developed packages and offering training through virtual workshops and Research Experiences for Undergraduates (REU) programs, the project fosters inclusive education and expands access to cutting-edge materials in science research. This work promotes the progress of science by enabling high-precision simulations, supporting national efforts in technology innovation, and training a broad range of students in computational materials research. The project develops a unified, extensible software framework that integrates Density Functional Theory (DFT), DFT+U, and Dynamical Mean Field Th