The unstructured mesh (UM)–based Monte Carlo (MC) method can utilize modern computer-aided-design/computer-aided-engineering platforms to obtain geometric models with reduced human effort and is capable of generating high-resolution tally data. This approach presents a significant advantage over the traditional Constructive Solid Geometry (CSG)–based MC method in handling complex geometries and conducting multiphysics calculations. In this study, the UM-based MC calculation capability was developed in the MC code NECP-MCX. On this basis, an automatic UM-based Consistent Adjoint-Driven Importance Sampling (CADIS) method was further studied and implemented in which the adjoint deterministic calculation, forward MC calculation, and variance reduction (VR) parameter generation were performed on the unified UM model. To achieve this, the discrete ordinates (SN)–Discontinuous Finite Element Method (DFEM) code NECP-SUN was embedded into NECP-MCX as the adjoint transport solver. Validations of the developed code and evaluations of the VR performance of the UM-based CADIS method were conducted on the Pool Critical Assembly (PCA) Replica benchmark and H. B. Robinson Unit 2 (HBR-2) benchmark. The numerical results indicated that the developed UM-based particle tracking capability achieved comparable accuracy to the CSG-based approach. Furthermore, compared to the traditional CADIS method, the UM-based CADIS method demonstrated higher figure-of-merit (FOM) values (3.5 to 44 times higher for the PCA Replica benchmark and 2.22 to 2.92 times higher for the HBR-2 benchmark), highlighting the superior VR performance of the UM-based CADIS method over the traditional CADIS method.