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Multidisciplinary Design Optimization (MDO) is an area in engineering design which has been growing rapidly in terms of applications in the last few decades, aircraft design being no exception to that. The application of MDO to aircraft and more specifically, wing design, presents many challenges, since disciplines like aerodynamics and structures have to be combined and interact. The level to which this interaction is implemented depends only on how much one is willing to pay in terms of computational cost. The objective of the current work is therefore to develop a simplified MDO tool, suitable for the preliminary design of aircraft wings. At the same time, versatility in the definition of optimization problems (in terms of design variables, constraints and objective function) is given great attention. At the same time, modularity will ensure that this framework is upgradeable with higher-fidelity and/or more capable modules. The disciplines that were chosen for interaction were aerodynamics and structures/ aeroelasticity, though more data can be extracted from their results in order to perform other types of analyses. The aerodynamics module employs a Vortex Lattice code developed specifically for the current implementation of the tool. The structural module is based on Equivalent Plate model theory. The fluid structure interaction is simply one-way, wherein the aerodynamics loads are passed on to the structural analyzer for computation of the static deformation. Semi-empirical relations are then used to estimate the flutter speed. The optimizer, which controls the activity of the other modules, makes use of a gradient based algorithm (Sequential Quadratic Programming) to search for a local minimum of a user defined objective function. Among the myriad of MDO strategies available, two are chosen to exemplify the modularity of the tool developed: Multidiscipline Feasible (MDF) and Sequential Optimization (SO), and their results are compared. Several case studies are analyzed to cover a broad spectrum of the capabilities of the framework. Because user interaction is of prime concern in design optimization, a graphical interface (GUI) of the tool is presented. Its advantages in terms of the set up of optimization problems and post-processing of results are made clear. In conclusion, some topics for future work regarding the expansion and improvement of the features of the application are noted.