To deploy Micro Aerial Vehicles (MAVs) in real-world applications, there is a need for online methods to cope with uncertainties in localization and external disturbances. In this article, we propose a set of novel real-time embedded Nonlinear Model Predictive Control (NMPC) and Nonlinear Moving Horizon Estimation (NMHE) modules for MAV based external disturbance rejection. The NMPC and NMHE are based on the dynamic model of the MAV, thus, avoiding the need for system identification and creating specific aerodynamic models, a benefit that results in a generic solution capable of being independent of the type of the MAVs. As it will be presented, the NMHE estimates the external forces, while the NMPC generates thrust and attitude commands for the low-level controller to compensate the various disturbances that could occur, such as wind gusts, tethered payload, and varying center of gravity. The proposed method is evaluated extensively in multiple experimental results that include the scenarios of position hold against an actuating wind-wall, adding payload, and changing the MAV’s arm configurations.