Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have emerged as transformative materials that consistently captivated scientists across various disciplines, renowned for their exceptional attributes such as large specific surface area, structural tunability, high crystallinity, and precisely-defined accessible porous architectures. Recent advancements in synthetic strategies have facilitated the engineering of MOF/COF hybrid constructs by integrating these frameworks, yielding a superior class of porous materials with synergistic characteristics. This review presents a comprehensive overview of state-of-the-art design for diverse MOF-COF heterostructures and hybrid variants alongside their innovative fabrication methodologies. It systematically classifies the diverse MOF/COF hybrid architectures, thereby unifying all established variants within a unified conceptual framework. Distinct from prior studies, this article combines the various fabrication approaches with a comparative assessment of their structural configurations, key attributes, synthetic feasibility, inherent advantages and limitations, and application prospects. Addressing a critical gap in the literature, it also comprehensively examines the characterization techniques employed, encompassing structural, morphological, thermal, and elemental analyses, to elucidate a detailed understanding of this exciting porous family. Considerable efforts have been dedicated to unravelling the interfacial chemistries that enable the synergistic integration of the complementary attributes of MOFs and COFs. Moreover, this study systematically highlights the pioneering advancements spanning catalysis-such as molecular catalysis, photocatalysis, and energy-transfer photocatalysis-as well as broader areas, including chemical sensing, gas adsorption and separation, biosensing, tribology, and biomedical technologies. Finally, the existing challenges and future directions for MOF/COF composites are sketched, emphasizing the need to enhance chemical stability, interfacial electronic coupling, and structural versatility through innovative linkages, advanced heterostructures, and tailored architectures. The integration of machine learning and data-driven approaches will expediate the rational design of hybrids tailored for catalysis, energy storage, sensing, and separation, while leveraging synergistic interactions and emerging synthetic paradigms will unlock multifunctional platforms for a broad spectrum of high-impact cross-disciplinary applications.