In today’s fast-paced world, people frequently experience high levels of emotional stress and struggle to access personalized mental health support. Traditional mental health services often face challenges such as limited accessibility and a generalized approach, which can overlook individual emotional nuances. This one-size-fits-all method may fail to address the specific needs of individuals. The need for more responsive and individualized mental health resources has never been greater, highlighting the importance of innovative solutions that offer contextually relevant and personalized care. The Srimad Bhagavad Gita, a timeless spiritual text, offers profound teachings on managing emotions, finding purpose and maintaining balance in life. This project aims to develop a Mental Health Conversational Assistant that provides users with motivational responses rooted in the wisdom of the Bhagavad Gita. This chatbot leverages NLP and NLU to detect both the emotional state and the intent behind user queries. It uses advanced techniques like emotion detection and semantic understanding to analyze user input and respond with relevant verses from the Bhagavad Gita. By integrating Hugging Face’s emotion detection models and sentence-transformer embeddings, chatbot is capable of providing tailored, contextually relevant verses from Bhagavad Gita that match both the user’s emotions and the meaning of their queries.