  We study a sequence of $N-$particle mean-field systems, each driven by $N$
simple point processes $Z^{N,i}$ in a random environment. Each $Z^{N,i}$ has
the same intensity $(f(X^N_{t-}))_t$ and at every jump time of $Z^{N,i},$ the
process $X^N$ does a jump of height $U_i/\sqrt{N}$ where the $U_i$ are
disordered centered random variables attached to each particle. We prove the
convergence in distribution of $X^N$ to some limit process $\bar X$ that is
solution to an SDE with a random environment given by a Gaussian variable, with
a convergence speed for the finite-dimensional distributions. This Gaussian
variable is created by a CLT as the limit of the patial sums of the $U_i.$ To
prove this result, we use a coupling for the classical CLT relying on the
result of [Koml\'os, Major and Tusn\'ady (1976)], that allows to compare the
conditional distributions of $X^N$ and $\bar X$ given the random environment,
with the same Markovian technics as the ones used in [Erny, L\"ocherbach and
Loukianova (2022)].
