IndoorR2X introduces a novel benchmark and simulation framework for LLM-driven multi-robot task planning in indoor environments. The system enables Robot-to-Everything communication by integrating observations from mobile robots and static IoT sensors like cameras to construct a global semantic state. This approach overcomes partial observability challenges that traditional R2R communication faces, reducing redundant exploration and enabling scalable scene understanding. The framework provides configurable simulation environments, sensor layouts, robot teams, and task suites for evaluating coordinated indoor robot operations.