Fluorescence microscopy in combination with implanting a chronic window enables the consecutive in-vivo monitoring of cellular activity in the brain over long time periods. To handle both, the standardized and reproduceable analysis of microglia process motility and the resulting large amount of data, we present the open-source pipeline MotilA. MotilA provides fully automatic processing of multiple time-lapse image stacks. After pre-processing the data including registration, denoising, histogram equalization, image projection and binarization, MotilA calculates the motility of microglia processes or other cells by assessing the pixel variation between the individual time points, i.e., by calculating and comparing stable, gained and lost pixels. MotilA is able to process both, single- and multi-channel image stacks, including optional spectral unmixing. Batch processing image stacks of an entire microscopy campaign, the MotilA post-hoc analysis presents the resulting cellular motility over time and groups. To benchmark the performance of MotilA we compare our results with the manually assessed motility of a set of hippocampal microglial cells in the mouse brain. We demonstrate that MotilA reproduces the human detected motility in significant shorter time, ruling out any human bias and increasing the reliability of the results due to the standardization of the analysis.