The spatial-omics field continues to rapidly grow, where new technologies, protocols and analytic tools are released almost weekly. Existing methods now enable researchers to generate high-quality data for any molecular modality of interest. While combining these spatial multi-modal data opens an unprecedented opportunity to comprehensively explore molecular regulation at transcriptional, translational and metabolic levels, computational methods to do so are lacking. This is especially true for spatial metabolomics, which is still in its early stage of development, but has already generated powerful data with a great potential for revealing biological insights. Here, we introduce SpaMTP, an R-based open-source toolbox designed for the comprehensive exploration and analysis of spatial metabolomics data. Additional to a wide-range of user-friendly and interoperable functionalities, SpaMTP is the first software package to provide integrative spatial multi-omics data analysis. In this presentation, the SpaMTP capabilities will be demonstrated by analysing medulloblastoma samples, which have been treated with a possible clinical drug candidate. Analyses using SpaMTP identified key transcriptional and metabolic changes associated with cell expressing the drug compared to untreated cells, allowing us to comprehensively understand the relative activation pathways by which the drug functions within medulloblastoma. We expect that SpaMTP will be a valuable tool for the metabolomics, single-cell and spatial omics communities.