The classical model of mast cell secretory granule formation suggests that newly synthesized secretory mediators, transported from the rough endoplasmic reticulum to the Golgi complex, undergo post-transitional modification and are packaged for secretion by condensation within membrane-bound granules of unit size. These unit granules may fuse with other granules to form larger granules that reside in the cytoplasm until secreted. A novel stochastic model for mast cell granule growth and elimination (G&E) as well as inventory management is presented. Resorting to a statistical mechanics approach in which SNAP (Soluble NSF Attachment Protein) REceptor (SNARE) components are viewed as interacting particles, the G&E model provides a simple ‘nano-machine’ of SNARE self-aggregation that can perform granule growth and secretion. Granule stock is maintained as a buffer to meet uncertainty in demand by the extracellular environment and to serve as source of supply during the lead time to produce granules of adaptive content. Experimental work, mathematical calculations, statistical modeling and a rationale for the emergence of nearly last-in, first out inventory management, are discussed.