Micro Air Vehicles are aircraft with dimensions less than 15cm which are used for surveillance, reconnaissance, aerial photography etc. Micro Air Vehicles (MAV) can be broadly classified into three types: fixed wing, rotary wing and nature inspired/bio-mimicking MAVs. MAVs generally operate at Reynolds number in the order of ~1e5 and have a mass ~100g. Due to the size restrictions, fixed wing MAVs tend to have low aspect ratio wings and their design requires optimum aerodynamic efficiency at low Re flows over the wing, optimum weight of the structure and components such as sources of power and propulsion. Multi-disciplinary Design Optimization (MDO) involves application of optimization techniques by incorporating requirements from a number of disciplines which govern the design evolution of any component or process. Design of aircraft/Aerospace vehicle and its components involves inputs from various disciplines such as aerodynamics, structures, propulsion systems, flight controls, layout etc., to name a few. Designing such components by incorporating all relevant disciplines simultaneously would yield in a better design in comparison to a design evolved by optimizing each discipline simultaneously as the latter does not incorporate the effect of interaction between the different disciplines. In this work, a Python based MDO framework to develop a parametric geometry for a fixed wing MAV, incorporate free and open source analysis tools of various disciplines for designing the planform of a fixed wing Micro Air Vehicle (MAV) and study the nature of interactions between different disciplines in evolving a fixed wing MAV planform is attempted.