Tropical cyclones (TCs) are among the most destructive weather events. To better understand them, numerical weather models are used to simulate those systems, which are then detected by designated tracking algorithms. This is generally done in a two-step process, where the tracking process is done in an off-line manner, after the weather simulation has terminated. This requires to save diagnostics data over the whole simulated domain, which are then processed by the tracking program and then by a processing tool to extract diagnostics quantities around the tracks. This presents the inconvenience to require massive amounts of intermediate data, which can rapidly become prohibitively large, with increasing spatial and temporal resolution, especially in the context of performing ensemble simulations. In this paper, we present an innovative solution to this problem, by implementing an on-line version of the Epimetheus (Enz et al., 2023) tracking algorithm: the TC detection is performed directly within the numerical weather prediction and climate model ICON and any diagnosed quantity from the ICON model can be output in a user-defined region around each detected TC centre. We conduct a detailed comparison analysis between the off-line and the on-line tracking algorithm versions. Besides the already exposed gain in storage footprint, we show that the on-line version allows a higher track detection calling frequency, yielding more accurate results.