The future integration of various energy vectors into a single multi-energy network is crucial for enhancing flexibility, efficiency, and sustainability of the entire energy system. This challenge is closely associated with the digitization of networks, as it requires integrated management of data not only from various internal utility systems (GIS, asset management, DMS) but also related to different energy vectors. This article introduces a semantic, modular, open-source platform based on international standards to manage and study multi-energy networks: the Multi Energy Semantic Platform (MESP). The architecture, based on Kubernetes and microservices, ensures synergies between semantic web technologies and big data/machine learning algorithms. To demonstrate the platform’s capabilities, a real case study for the city of Milan is presented. This example describes the electric distribution network and district heating networks using a semantic model (based on IEC CIM), with respective points of exchange identified and geographically visualized. Both utilities and universities can benefit from this open-source platform, which supports easy integration of artificial intelligence algorithms and is adaptable to the needs of different use cases. Furthermore, MESP can assist in managing operations for energy communities or small electric cooperatives that may not afford large investments in terms of finances and human resources.