Secreted molecules mediate interactions with the environment and the surrounding microbiome, and numerous biotechnological applications take advantage of the secretion machinery. Bacterial protein secretion has mainly been studied in pathogenic and polymer-degrading bacteria due to their importance in human health and the environment. However, many globally abundant prokaryotes, such as cyanobacteria, remain understudied. This is mainly due to challenges associated to mass spectrometric analysis of extracellular samples where proteins are highly diluted in matrices rich is salts, lipids and polysaccharides. Here, we introduce EXCRETE (enhanced exoproteome characterization by mass spectrometry), a workflow that enables in-depth analysis of microbial exoproteomes from only a few hundred microliters of culture medium. EXCRETE benchmarking demonstrated an almost 60% increase in identified exoproteins in less than a third of the time typically requited to prepare exoproteomics samples. We then show that EXCRETE can be miniaturized and adapted to a 96-well-plate high-throughput format. Finally, EXCRETE was then applied to the exoproteome of cyanobacteria from different habitats: the freshwater Synechocystis sp. PCC 6803; the marine Synechococcus sp. PCC 11901; and the terrestrial Nostoc punctiforme PCC 73102. Our approach identified up to 7.5x more exoproteins than previous studies, thus demonstrating the robustness of the method independent of the composition of the medium or extracellular matrix. Functional analysis of the three secretomes revealed a predominance of proteins involved in cell envelope maintenance, protein turnover, and nutrient acquisition. Collectively, these findings challenge the general belief that cyanobacteria lack secretory proteins and point to a functional conservation of the secretome across freshwater, marine and terrestrial species. This workflow should be broadly applicable to microbes from a wide range of habitats, with the potential to open new avenues of investigation in microbial exoproteomics.