Assume that $\det\Sigma\ne0$. Then the random matrix $X$ is of rank $m$ almost surely (a.s.). So, a.s. the Moore--Penrose inverse of $X$ is $X^+=X^\top(XX^\top)^{-1}$ and hence $$X^+X=X^\top(XX^\top)^{-1}X.$$ Letting $Z$ be the matrix with rows $z_i:=\Sigma^{-1/2}x_i$, we see that the $z_i$'s are iid $N(0,I_n)$, and $$X^+X=X^\top(XX^\top)^{-1}X=Z^\top(ZZ^\top)^{-1}Z=Z^+Z.$$ So, the problem reduces to the case when $\Sigma=I_n$ -- which, as you noted, is easy.
Thus, the answer is $$EX^+X=\frac mn\,I_n,$$ as long as $\det\Sigma\ne0$.