We present BloomTutor, an Intelligent Tutoring System (ITS) that integrates Retrieval-Augmented Generation (RAG) with Bloom's Taxonomy to support learners in exploring, revising, or querying specific topics within a predefined subject or course. Our system retrieves relevant course materials based on user queries, segments them into concise chunks, and generates questions aligned with cognitive levels. Learner responses guide real-time adjustments in question difficulty, enabling progression toward higher-order thinking or reinforcement of foundational concepts. Unlike most ITS that rely on fixed question banks, Bloom-Tutor generates context-specific questions in real time, allowing greater coverage and responsiveness to diverse learner queries and progress.