The MCMC procedure (PROC MCMC) is a general purpose Markov chain Monte Carlo (MCMC) simulation procedure that is designed to do Bayesian analyses. PROC MCMC is a flexible simulation-based procedure that is suitable for fitting a wide range of Bayesian models. To use the procedure, you need to specify a likelihood function for the data and a prior distribution for the parameters. PROC MCMC then obtains samples from the corresponding posterior distributions, produces summary and diagnostic statistics, and saves the posterior samples in an output data set that can be used for further analysis.
PROC MCMC is unlike most other SAS/STAT procedures in that the nature of the statistical inference is Bayesian. The procedure derives inferences from simulation rather than through analytic or numerical methods. The model specification is similar to PROC NLIN, and PROC MCMC shares much of the syntax of PROC NLMIXED.
More can be found from SAS/STAT 9.2 documentation: The MCMC Procedure