Maybe try for something even simpler than MNIST, so we can get the great immediate feedback effect of http://playground.tensorflow.org, which I consider the important aspect for learnability?
Hidden units for discriminator layers - 100, 40, 2.
Generator layers - 40, 100, 768, then "reshape" into 28x28x1.
By playing around with it, the results I got from fully connected were nowhere near as good as the results I got from convolutional.
In Israel we have a classic song that goes "if you're cooking spaghetti and the water doesn't boil, how about turning the stove on, because that's what everybody does"
(at the time of writing, the HN post points to the demo)