KM3NeT is an underwater neutrino detector currently under construction. Since the installation of its first Detection Unit in 2015, it has been continuously collecting data. Due to its complex design, a 3D array of sensors, an Acoustic Positioning System (APS) was developed to monitor the position of each sensor. Given the increasing number of acoustic sensors used for the APS, both receivers and emitters, a solution was implemented to check their status. In this contribution, a monitoring tool for this instrumentation is presented, capable of evaluating its status at both the data and operational levels. For effective monitoring, it is crucial to associate the signal recorded by a receiver with the corresponding transmitter. The Acoustic Data Filter (ADF) performs a cross-correlation between the signals retained in a buffer and those emitted by each installed emitter. It saves the maximum peak value and its associated time of arrival for each expected signal. However, the growing number of beacons complicates the differentiation of corresponding transmitters due to the huge amount of data recorded by the ADF, needing post-processing. To address this challenge, a monitoring tool that analyzes the internal clock of each emitter to distinguish and filter the data collected by the ADF is developed. This tool has tested highly effective in verifying the correct operation of all acoustic devices deployed at sea. The acoustic monitoring graphical output produced for each data slot facilitates quick failure detection, enabling a swift response. Last but not least, the tool is modular and scalable, adapting to the addition or removal of sensors from the detector.