how do I decide the best number of observations in MLE?

Of course, in MLE, if we collect more and more observations data, MLE
will perform better and better.

But is there a way to find a bound on parameter estimate errors in
order to decide when to stop collect data/observations, say 1000
observations are great, but 500 observations is good enough...

Thanks!