Increasing demand for faster and more agile Unmanned Aerial Vehicles (UAVs, drones) is observed in many scenarios, including but not limited to medical supply or Search-and-Rescue (SAR) missions. Exceptional maneuverability is critical for robust obstacle avoidance during autonomous flights. A novel modification to the Model Predictive Controller (MPC) is proposed, which drastically improves the speed of the attitude controller of our quadcopter drone. The modified MPC is suitable for the onboard microcontroller and the 400 Hz main control loop. The peak and total energy consumption and the performance of the attitude controllers are assessed: the modified MPC and the default Proportional-Integral-Derivative (PID). The tests were conducted in a custom-implemented Flight Mode in the ArduCopter software stack, securing the drone in a test harness, which guarantees the experiments are repetitive. The ultimate MPC greatly increases maneuverability of the drone and may inspire more research related to faster obstacle avoidance and new types of hybrid attitude controllers to balance the agility and the power consumption.