The Loop Current (LC), along with its associated meanders, eddies (LCEs), and cyclonic frontal eddies (LCFEs), plays a major role in the Gulf of Mexico and has been extensively studied over the past decade, with several field campaigns. During the recent 6-month collaborative GRand Adaptive Sampling Experiment (GRASE; April to September 2025), we employed our MIT Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS), including Error Subspace Statistical Estimation (ESSE) large-ensemble forecasting to provide real-time probabilistic forecasts. We describe the evolution of ocean features and evaluate the predictive skill of our forecasts compared to independent data. We present our probabilistic glider reachability and optimal path planning forecasts. This includes the use of reachability and heading forecasts for optimal deployment, feature sampling and tracking, and recovery of multiple gliders. We show that the actual glider tracks remain within our forecast reachability fronts and that headings could be followed in real-time. We demonstrate the use of our information-theoretic methodology for optimal adaptive sampling with gliders and floats, where we maximize information about specific future properties of the LC, LCEs, and LCFEs. We issued reachability forecasts for floats and modified 3D Lagrangian flow maps to account for float motions. We forecast float transports during several periods, highlighting how float deployment regions remain coherent or are being distorted, especially how the transport of floats on the edges of LCFEs can be affected by shear and turbulence. Lastly, we illustrate our real-time clustering of the large-ensemble probabilistic LCE forecasts and how we showed that an LCE detachment in June/early July 2025 was very unlikely. This work is in collaboration with the whole GRASE team.