Minimally invasive surgeries are less likely to cause an infection, bleeding, or postoperative complications. They can, however, only be accomplished with sufficient skill and experience on the part of the surgeon. The present study mainly aims to provide the context for the remote control of laparoscopic devices and improve the performance of minimally invasive surgeries so that all patients can have access to skilled surgeons beyond geographical limitations. The leap motion controller first acquired the fine movements of the surgeons' hands, the position and gesture of the fingers, and an awareness of the alterations of the corresponding angles and coordinates, which were required in every instant. A 5-DOF robot is built and controlled using data from the Leap Motion sensor to control the laparoscopic grasper. These data, which represent the surgeon's hand coordinates, are wirelessly input to the Raspberry Pi board via TCP and then transmitted to the robot's actuators after being substituted into the corresponding kinematic equations. Encoders embedded in the joints of the robot are used for closed-loop control using a PID controller with a feed-forward compensator. The average accuracy of the prototype robot was calculated to be better than 4° by computing the RMSE of every joint. Moreover, the accuracy of the lead screw mechanism was obtained to be 0.4141 mm in opening and 0.6162 mm in closing the grasper jaws. Additionally, in experimental tests, the Leap Motion sensor's error was discovered to be up to 5 mm, and the viability of lowering this error by using Kalman filtering was investigated.