College students face unique mental health challenges that are often inadequately addressed by existing technologies. This paper presents a design case study focused on developing a mental health support tool tailored for college students. We begin by analyzing key findings from an online survey with students and counseling center staff, which identified prevalent barriers and needs. Based on these insights, we outline an iterative design process involving brainstorming, prototyping, and refining features to enhance user engagement and support. Our final design includes dynamically generated survey questions, personalized content recommendations, and an adaptable interface, aiming to overcome limitations of static assessments and lack of customization in current tools. We also discuss future directions, emphasizing the integration of real-time campus health data, advanced user profiling, and machine learning algorithms to provide a more effective and personalized mental health support experience for students. This work contributes to advancing mental health technology by addressing identified gaps and proposing innovative solutions.