In the telecommunication sector, optimizing network performance is crucial, particularly in code assignment or code planning, where improper execution can lead to call drops. This tutorial explores solving the code assignment problem in telecommunication networks using graph algorithms with Memgraph and its MAGE library. The process involves modeling networks as graphs, where nodes represent base stations and edges indicate potential signal interference, and employing graph coloring to assign unique codes to nearby base stations to prevent interference. Memgraph Lab offers visualization tools to map these networks, and the MAGE library provides prebuilt algorithms for efficient graph coloring, inspired by Quantum Annealing, a metaheuristic approach to optimization. The tutorial guides users through importing datasets, running graph coloring procedures, and visualizing results, emphasizing the importance of correctly setting parameters to minimize errors. Additionally, it highlights the benefits of using Memgraph for persistent data storage and advanced analytics, while encouraging contributions to the open-source MAGE library for further community advancement.