This paper introduces a new tensor network ansatz called CAMPS (Clifford Augmented Matrix Product States), which combines the strengths of the Density Matrix Renormalization Group (DMRG) and Clifford circuits. DMRG is a powerful method for simulating one-dimensional quantum many-body systems, but it faces challenges when applied to two-dimensional systems due to limited entanglement in the wave-function ansatz. Clifford circuits, on the other hand, can simulate states with high entanglement but are limited to stabilizer states. CAMPS integrates Clifford circuits into the DMRG framework, enhancing simulation accuracy with minimal additional computational cost. The wave function of CAMPS is obtained by applying Clifford circuits to the MPS (Matrix Product States) wave function. This integration allows for the efficient simulation of two-dimensional quantum systems by leveraging the entanglement properties of Clifford circuits. The paper demonstrates that CAMPS maintains nearly the same computational complexity as DMRG while significantly improving simulation accuracy. It is shown that CAMPS can achieve high precision in simulating the 2D J1-J2 Heisenberg model, with relative errors reduced by a factor of 5 for a lattice size of 10x10 and bond dimension D=3000. The paper also discusses the entanglement entropy in the MPS part of CAMPS and shows that it is smaller compared to pure MPS calculations. A critical bond-dimension threshold is identified, beyond which the entanglement entropy in the MPS part of CAMPS saturates rapidly, while in pure MPS calculations, it continues to increase with bond dimension. This indicates that CAMPS can converge more rapidly once the non-stabilizerness of the state is converged. The paper highlights the advantages of CAMPS over pure MPS calculations, as it allows the MPS component to deal solely with the non-stabilizerness. The framework is also discussed in terms of its potential for extension to other numerical simulation methods and its application to fermionic degrees of freedom in the future. The study demonstrates the effectiveness of CAMPS in unraveling the mysteries of 2D quantum systems and its potential to influence the numerical investigation of quantum many-body systems.This paper introduces a new tensor network ansatz called CAMPS (Clifford Augmented Matrix Product States), which combines the strengths of the Density Matrix Renormalization Group (DMRG) and Clifford circuits. DMRG is a powerful method for simulating one-dimensional quantum many-body systems, but it faces challenges when applied to two-dimensional systems due to limited entanglement in the wave-function ansatz. Clifford circuits, on the other hand, can simulate states with high entanglement but are limited to stabilizer states. CAMPS integrates Clifford circuits into the DMRG framework, enhancing simulation accuracy with minimal additional computational cost. The wave function of CAMPS is obtained by applying Clifford circuits to the MPS (Matrix Product States) wave function. This integration allows for the efficient simulation of two-dimensional quantum systems by leveraging the entanglement properties of Clifford circuits. The paper demonstrates that CAMPS maintains nearly the same computational complexity as DMRG while significantly improving simulation accuracy. It is shown that CAMPS can achieve high precision in simulating the 2D J1-J2 Heisenberg model, with relative errors reduced by a factor of 5 for a lattice size of 10x10 and bond dimension D=3000. The paper also discusses the entanglement entropy in the MPS part of CAMPS and shows that it is smaller compared to pure MPS calculations. A critical bond-dimension threshold is identified, beyond which the entanglement entropy in the MPS part of CAMPS saturates rapidly, while in pure MPS calculations, it continues to increase with bond dimension. This indicates that CAMPS can converge more rapidly once the non-stabilizerness of the state is converged. The paper highlights the advantages of CAMPS over pure MPS calculations, as it allows the MPS component to deal solely with the non-stabilizerness. The framework is also discussed in terms of its potential for extension to other numerical simulation methods and its application to fermionic degrees of freedom in the future. The study demonstrates the effectiveness of CAMPS in unraveling the mysteries of 2D quantum systems and its potential to influence the numerical investigation of quantum many-body systems.