Brain-Computer Interface (BCI) technology has emerged as a transformative approach for enabling direct communication between human cognition and robotic systems, particularly in rehabilitation and hazardous-environment applications. This paper presents ManoHastha, a low cost, non-invasive BCI-driven extendable robotic arm designed to convert neural intent into mechanical actuationusing Electroencephalography   (EEG)and Electrooculography (EOG) signals. The proposed system integrates a BioAmp EXG Pill for bio-signal acquisition, an Arduino Nano for signal conditioning and analog to digital conversion, and an ESP32 microcontroller for wireless communication and robotic control. The robotic manipulator operates based on voluntary eye blinks and sustained attention levels, allowing users  to  perform  reach-and-grab  operations

without physical interaction. A hybrid processing architecture was implemented to reduce latency and improve operational reliability. Experimental evaluation demonstrated accurate detection of intentional blink patterns and stable attention- based control with an overall response latency of approximately 125 ms, ensuring near real-time performance. The complete system was developed with a total hardware cost below₹10,000, making advanced neuro-robotic technology more accessible for educational, assistive, and industrial safety applications. The results confirm that ManoHastha provides a reliable and affordable framework for practical BCI-enabled robotic manipulation