In this work, we present the Clenching Upper-Limb Force Feedback Device (CUFF), integrated with the SoftHand Pro robotic hand. Grasping an object is a complex action that relies on sensory feedback. While prosthetic hands assist with mechanical performance, they often lack adequate sensory feedback. Providing feedback about a prosthetic hand’s grasp force is crucial for individuals with limb loss. We tested the CUFF system, controlled via myoelectrics of the forearm muscles, with five participants with limb loss and nineteen able-bodied participants. They completed a constrained grasping task (with and without feedback) requiring modulation of the grasp to reach a target force, with vision and hearing significantly limited. Data were analyzed using generalized linear models and Functional Principal Component Analysis (fPCA). CUFF feedback improved the able-bodied participants’ ability to achieve the target grasp force and enhanced grasp precision for participants with limb loss who typically use body-powered prostheses, as well as for a subset of able-bodied participants. Further testing is needed to determine if CUFF feedback can accelerate the mastery of myoelectric control or benefit specific patient sub-groups.