Reversible jump MCMC for variable numbers of parameters used for Dirichlet process (DP) modeling of number of clusters is unlikely to work in practice. Clustering is hard enough already as a combinatorial problem. One thing you can do is take a large number of clusters relative to the data and then you can approximate the DP model. It will still be a challenge to fit, especially if the data is high dimensional and heterogeneous.