  This paper studies the numerical approximation for McKean-Vlasov stochastic
differential equations driven by L\'evy processes. We propose a tamed-adaptive
Euler-Maruyama scheme and consider its strong convergence in both finite and
infinite time horizons when applying for some classes of L\'evy-driven
McKean-Vlasov stochastic differential equations with non-globally Lipschitz
continuous and super-linearly growth drift and diffusion coefficients.
