Objectives: This work proposes a Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search (CS) method. Methods: It is acknowledged that CS exhibits several advantages which include fast convergence, higher efficiency using fewer tuning parameters. The paper outlines the concept of CS by highlighting the significance of the Levy flight in influencing the algorithm's convergence. The main equations that govern the behavior of the search are also explained. To justify CS as a viable MPPT option, a comprehensive assessment is carried out against two well established methods, namely Perturbed and Observed (P&O) and Particle Swarm Optimization (PSO). The evaluations include (1) gradual irradiance and temperature changes, (2) step change in irradiance and (3) rapid change in both irradiance and temperature. These tests are carried out for both large and medium-sized PV systems. Furthermore, the ability of the algorithm to handle the partial shading condition is demonstrated. Results: The results show that CS is capable of tracking MPP within 100-250 ms under various types of environmental change. Besides, the power loss in steady state due to MPP mismatch is only 0.000008%. Furthermore, it can handle the partial shading condition very efficiently. Conclusion: CS outperforms both P&O and PSO with respect to tracking capability, transient behavior and convergence. Practical implications: Due to these excellent features, it is envisaged that the CS can be suitably used as a MPPT, particularly for large PV system. (C) 2014 Elsevier Ltd. All rights reserved.