We study metric facility location with customer incompatibilities, where the clients assigned to each facility must satisfy prescribed independence constraints. We first consider the setting of facility-opening costs and where there is a single matroid $\mathcal M$ over the clients and the set of clients assigned to an open facility must be an independent set in $\mathcal M$. We develop a polynomial-time \((1+\sqrt{2}+ε)\)-approximation algorithm for this setting. We further obtain a polynomial-time \((15+ε)\)-approximation algorithm for the case of non-uniform facility-opening costs when $\mathcal M$ is a partition matroid that only permits $b_g$ clients to be assigned to a facility for each group $g$ in the partition. Both settings are substantial generalizations of Capacitated Facility Location with uniform capacities. Our algorithms are based on local search using add, delete, and single-swap operations. As with CFL, bounding the connection cost is reasonably straightforward using supermodularity of the minimum connection-cost function. However, bounding the facility opening costs requires novel arguments in both cases. We use a ``compression'' argument based on matroid exchange principles to identify a subset of the locally opened facilities whose size is no larger than that of an optimal facility set. The opening costs of facilities outside this subset can be bounded using supermodularity, while bounding the costs of the remaining facilities requires different arguments. It is natural to consider a variant where each possible facility $i$ has its own matroid $\mathcal M_i$ defining the subsets of clients it can feasibly serve. We also show problem is at least as hard to approximate as Set Cover even if all $\mathcal M_i$ are partition matroids that have the same partition of clients, just different group bounds $b_g$.

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