Why do you say that? Metropolis is infamous for generating very auto-correlated draws and taking many more steps (and logp evaluations) to achieve the same number of effective sample size as modern alternatives like NUTS that can exploit gradient information.
Perhaps you meant custom Gibbs samplers that can take random draws from the conditional posterior distributions without any rejection steps?