As large language models (LLMs) become increasingly integrated into educational settings, concerns about academic integrity, ethical usage, and student engagement are becoming more prominent. While these AI tools can effectively provide personalized learning experiences and support diverse student needs, they also risk overreliance and promote unethical academic practices if used without appropriate safeguards. This paper presents a novel approach that integrates an LLM-based assistant directly into a learning management system (LMS) with carefully designed constraints to encourage active learning, reduce misuse, and preserve academic integrity. We establish core design principles to address the challenges associated with LLMs in education and provide a detailed description of our system's architecture. Additionally, we conduct a pilot study to assess the tool's impact on student learning and gather feedback for further improvements. A prototype of the tool is publicly available on Github.