This paper describes an approach to building a cost-effective and research grade visualinertial odometry aided vertical taking-off and landing (VTOL) platform. We utilize an off-the-shelf visual-inertial sensor, an onboard computer, and a quadrotor platform that are factory-calibrated and mass-produced, thereby sharing similar hardware and sensor specifications (e.g., mass, dimensions, intrinsic and extrinsic of camera-IMU systems, and signal-to-noise ratio). We then perform system calibration and identification enabling the use of our visual-inertial odometry, multi-sensor fusion, and model predictive control frameworks with the off-the-shelf products. This approach partially circumvents the tedious parameter tuning procedures required to build a full system. The complete system is evaluated extensively both indoors using a motion capture system and outdoors using a laser tracker while performing hover and step responses, and trajectory following tasks in the presence of external wind disturbances. We achieve root-mean-square (RMS) pose errors of 0.036 m with respect to reference hover trajectories. We also conduct relatively long distance (≈180 m) experiments on a farm site, demonstrating 0.82% drift error of the total flight distance. This paper conveys the insights we acquired about the platform and sensor module and offers open-source code with tutorial documentation to the community.