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Context. An automatic tool to derive structural parameters of semi-resolvedstar clusters located in crowded stellar fields in nearby galaxies is neededfor homogeneous processing of archival frames.  Aims. We have developed a program that automatically derives the structuralparameters of star clusters and estimates errors by accounting for individualstars and variable sky background.  Methods. Models of observed frames consist of the cluster's surfacebrightness distribution, convolved with a point spread function; the stars,represented by the same point spread function; and a smoothly variable skybackground. The cluster's model is fitted within a large radius by using theLevenberg-Marquardt and Markov chain Monte Carlo algorithms to derivestructural parameters, the flux of the cluster, and individual fluxes of allwell-resolved stars.  Results. FitClust, a program to derive structural parameters of semi-resolvedclusters in crowded stellar fields, was developed and is available for freeuse. The program was tested on simulated cluster frames, and was used tomeasure clusters of the M31 galaxy in Subaru Suprime-Cam frames.  Conclusions. Accounting for bright resolved stars and variable sky backgroundsignificantly improves the accuracy of derived structural parameters of starclusters. However, their uncertainty remains dominated by the stochastic noiseof unresolved stars.

Deriving structural parameters of semi-resolved star clusters. FitClust: a program for crowded fields