The concept of smart and sustainable city has been on the agenda for the last decade. Smart governance is about the use of innovation for supporting enhanced decision making and planning to make a city smart, by leveraging on Key Performance Indicators (KPIs) as procedural tools. However, building processes and instruments able to evaluate smart cities is still a challenging task, due to the rigidity showed by the existing frameworks in the definition of KPIs and modeling of the subjects to be evaluated. Web-based platforms, excel spreadsheets or even cloud-based applications offer limited flexibility, if the stakeholder is interested not only in using but also in defining the pieces of the puzzle to be composed. Model-driven engineering offers great benefits with the right level of abstraction in multiple domains. In this paper we present a flexible architecture supporting a model-based approach for the KPIs assessment in smart cities. It identifies both required and optional components and functionalities needed for realizing the automatic KPIs assessment, while showing flexibility points allowing for different specification of the architecture, thus of the overall methodology.