Transit systems have encountered a radical change in the recent past as a result of the digital disruption. Consequently, traditional public transit systems no longer satisfy the diversified demands of passengers and hence, have been complemented by demand responsive transit solutions. However, we identify a lack of simulation tools developed to test and validate complex scenarios for real-time demand responsive public transit. Thus, in this paper, we propose a simulation framework, which combines complex scenario creation, optimization algorithm execution and result visualization using SUMO, an open source continuous simulator. In comparison to a state-of-the-art work, the proposed tool supports features such as varying vehicle capacity and driving range, immediate and advance passenger requests and maximum travel time constraints. Further, the framework follows a modular architecture that allows plug-and-play support for external modules.