High resolution Ultra High Field 7T imaging is highly prone towards involuntary motion artifacts. Fat Navigator based motion correction provides a robust solution but it is a retrospective correction method. In this study we present an online reconstruction method 3D GRE FatNavs with open-source reconstruction tool, Gadgetron. We improved the performance of the GRAPPA reconstruction pipeline in Gadgetron for fast online reconstruct FatNav. We also implemented a Python Gadget to perform fsl Flirt based co-registration through NiPype to produce motion parameters from the FatNav.