But the MT becomes entirely predictable after 624 iterations, at which point its entropy should be considered to be zero, but the subsequent distribution is still uniform.
The subsequent distribution is not, in fact, independently uniform.
Given 624 32-bit outputs $$V = V_1 \mathbin\| V_2 \mathbin\| \cdots \mathbin\| V_{624},$$ I can deterministically recover the Mersenne twister state by $$S(V) = \tau^{-1}(V_1) \mathbin\| \tau^{-1}(V_2) \mathbin\| \cdots \mathbin\| \tau^{-1}(V_{624}),$$ where $\tau$ is the tempering transform, and then compute the next output by deterministically running the generator $G$ on the recovered state $S(V)$. If the $V_i$ were independently uniformly distributed, we would have $$\Pr[V_{625} = G(S(V))] = 1/2^{32},$$ but if the $V_i$ are instead generated by the Mersenne twister with uniform random initial state, we have $$\Pr[V_{625} = G(S(V))] = 1.$$
This test—evaluate whether $V_{625} = G(S(V))$—will distinguish the Mersenne twister under a uniform random initial state from a uniform random string with high success rate.
Does this nonuniformity matter for the Monte Carlo physics simulation you're doing? Perhaps not: your physics model is unlikely to, by happenstance, interact with the Mersenne twister output generation function $G$ in a way that would be a problem, because physics itself is usually not adversarially trying to screw you up personally, no matter how much the years of pain in grad school might make it seem.
On the other hand, if there is an intelligent adversary, as we assume in cryptography, that intelligent adversary will exploit this relation to decipher your messages, steal your money by forging signatures, etc.
In other words, the Mersenne twister is designed to appear uniform to stupid algorithms that don't even know it's the Mersenne twister they're trying to distinguish, but falls flat on its face when it trips on an adversary who knows it's the Mersenne twister but just doesn't know the initial state.