If you are starting out with this you don’t really need to modify the MCMC settings, the defaults are often fine if not always the most efficient. The goal is to get enough to have reliable inferences on the parameters you care about so you would typically run a model, check the effective sample size and other diagnostic, and if those indicate that you need more samples you might need to increase the number of iterations and/or chains. The trade-off between chains and iterations is that chains run most efficiently as 1 chain per core but iterations always run serially. Running multiple chains from different starting values also gives you a chance to evaluate how reliably the code will initialize and converge to a given answer so people tend to take something like 4 chains as a default.
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