In the realm of human-computer interaction, the development of input devices accommodating diverse user needs is paramount. Traditional peripherals like mice and keyboards, though effective in typical settings, often falter in specialized conditions such as low-light environments. Addressing these constraints, this study introduces a novel gesture and voice-controlled mouse system. By leveraging real-time video and audio inputs, the system interprets user gestures and voice commands, eliminating reliance on conventional input tools. Additionally, it tackles unresolved interface design issues, striving to optimize user experience and broaden computing resource accessibility. Key to its functionality is the integration of MediaPipe for precise gesture recognition and natural language processing for voice command interpretation. Utilizing standard webcam and microphone hardware enables hands-free cursor control and command execution, particularly aiding users with mobility limitations. Methodologically, the system blends foundational theoretical principles with innovative design concepts for practical realization. Rigorous testing demonstrates a 90% accuracy rate in gesture recognition and a notable 60% accuracy in low-light conditions. Voice command interpretation achieves an impressive 95% accuracy across various accents and speech patterns, with a significant reduction in task completion time compared to conventional setups. This research underscores the potential of an affordable and adaptable technology, promising enhanced digital accessibility through ubiquitous webcam and microphone integration.