There is increasing evidence regarding the dependence of human health on actions performed using hands. In this paper, we propose an IoT-enabled framework for measuring hand strength based on pressure sensed from finger-tapping and finger-grip, also referred to as Finger-Tap and Grip Gram (FTGG). It performs sensing with the help of Clinical Mouse connected to IoT board which analyzes the static voltage from finger-grip and dynamic voltage from finger-tapping. The finger-grip strength is estimated using pressure differences between Tight and Hold postures for 20 s observation collected from 40 humans of diverse age groups. Similarly, finger-tapping is monitored by averaging the max and min voltages from Thumb, Middle, and Little fingers for 10 s window. We classify finger-tapping into High tap and Low tap based on the pressure transferred from fingertip to piezo discs. Experimental Analysis for FTGG using 40 users yields the following results: finger-grip strength is markedly different between identified user groups, tap strengths recorded for both groups varies across all three fingers, tap strength is highest for Thumb followed by Middle and Little finger, correlation monitored in the finger-grip data for mature group is higher than the young group, cross-correlation monitored for finger-tap strength data between young and mature groups is typically low. The IoT-enabled FTGG setup demonstrated in this paper holds promise in commercial usage entailing the monitoring and diagnosis of clinical issues related to hand strength.