In the thesis, we analyzed the behavior of the Monte Carlo tree search algorithm (MCTS) in the domain of simple chess endgames. We have implemented several heuristics for routing Monte Carlo simulations. Through the experimental process we have developed several versions of the program and analyzed the performance of individual heuristics and different configurations of the algorithm. The played moves were compared with perfect information using the Gaviota chess tablebases. As part of the software solutions, a graphical interface was created that allows monitoring the game against an intelligent agent. We have developed several programs to analyze the game, run simulations with different settings and visualize search trees and other results. We conducted an empirical study to determine the effect of the parameters of the MCTS algorithm and combinations of domain heuristics on the quality of play of the program.