Wildfire suppression technologies have become increasingly critical in the face of escalating climate challenges and growing threats to ecosystems and human settlements. While early detection remains essential for effective wildfire management, the speed and efficiency of suppression technologies are equally vital to containing the spread. Unmanned aerial vehicles (UAVs), particularly quadcopters, have been widely explored for tasks such as monitoring fire propagation and deploying fire-extinguishing balls. Despite their limitations in direct suppression due to harsh environmental conditions, quadcopters can be effective when deployed as part of an intelligent swarm system. However, aerial-only drones face serious constraints in hostile fire zones, prompting the need for innovative, ground-compatible drone designs. The main aim of this study to introduce a novel hybrid uncrewed system to the scientists in the field. The design is termed the Bimodal MorphoCopter (BMC), which incorporates a planar inverted slider-crank mechanism to enable seamless transformation between aerial (drone) and terrestrial (all-terrain vehicle, ATV) modes. The proposed mechanism offers morphable, bimodal functionality, allowing drones to switch modes and directly engage wildfires from the ground, particularly in areas surrounding settlements such as Los Angeles. To achieve this functionality, the retraction motion of the coupler through the output link must be transformed into a solely extension — a key mechanical challenge addressed in this research. The kinematic design problem is formulated and solved using the Bee Algorithm, an optimization technique inspired by the foraging behavior of honeybees. The results aim to enhance swarm-based wildfire intervention systems by providing robust, adaptive ground-air mobility in dynamic fire-prone environments.