Brief Action Planning (BAP) is a structured method rooted in motivational interviewing, designed to support individuals in adopting healthier behaviors. This paper explores the feasibility of using Large Language Models (LLMs) as conversational agents to deliver BAP without specialized training data or fine-tuning. By employing role-play prompting, we guided an LLM to simulate a health coach that facilitates goal-setting and action planning for sedentary lifestyles. The approach was tested in simulated conversations and user evaluations, examining adherence to BAP protocols and user experience. Results demonstrate both promise and limitations: while the LLM could replicate several key components of BAP, challenges remain in consistency and personalization. These findings highlight the potential of LLM-driven role-play as a complementary tool for scalable, time-efficient health interventions.