Context-Aware Recommender Systems (CARS) offer context-based suggestions that are particularly crucial in the tourism domain, where personalized experiences significantly enhance user satisfaction. However, the evaluation of CARS is a challenge, partly due to the scarce availability of appropriate datasets that fulfill a variety of evaluation purposes. For example, to evaluate CARS, we need datasets that incorporate context data, but in practice existing datasets provide very little contextual information. This paper presents AUTO-DataGenCARS+, a graphical user-oriented tool designed to generate synthetic data for evaluating both Recommender Systems and CARS. Some of the relevant features of the tool include: a flexible definition of user profiles, user, item and context schemas; a realistic generation of ratings and item attributes; the possibility to mix real and synthetic datasets; functionalities for analyzing and evaluating existing datasets; and an extendable architecture for advanced users. We illustrate the benefits of AUTO-DataGenCARS+ through several examples and experimental evaluations.