Storytelling is a powerful non-pharmacological intervention in care for People with Dementia (PwD), offering the opportunity of self-expression, emotional connection and identity preservation. However, creation of multimedia material to accompany such stories usually requires trained experts and a considerable effort, which limits scalability and personalization. This paper presents a modular system using Artificial Intelligence (AI) which, together with a social robot, aims to transform collaboratively written stories into personalized images and songs. Using a local Large Language Model (LLM) for prompt generation and external diffusion models for media synthesis, the system also supports an interactive feedback system in which users can refine the output. Because of ethical constraints related to data confidentiality, fully autonomous music generation was not implemented, however, the system allows users to generate music manually with any external AI model, automatically detecting the song and playing it in the storytelling interaction flow. The system was tested using simulated stories on consumer-grade hardware, as such confirming the feasibility of media generation in real time, while also respecting confidentiality. The results show strong alignment between the story content and generated visuals, supporting the system's potential to enrich dementia storytelling experiences in an ethical and accessible way.