Many real-world networks exhibit multi-scale organization, yet identifying nested structural patterns remains challenging. We introduce a recursive framework to uncover the hierarchical organization of networks by extracting and evaluating densely connected subgraphs, called local components. At each level, components are assessed based on modularity, stability, and minimum size before being further decomposed. We apply this method to 24 real-world networks from social, biological, and technological domains. The results show diverse hierarchical depths (from 1 to 5), with social networks typically exhibiting deeper and more complex structures. Our analysis highlights the relevance of mesoscopic decomposition for characterizing the internal architecture of networks and enables cross-domain comparisons of structural depth.