In the online metric traveling salesperson problem, $n$ points of a metric space arrive one by one and have to be placed (immediately and irrevocably) into empty cells of a size-$n$ array. The goal is to minimize the sum of distances between consecutive points in the array. This problem was introduced by Abrahamsen, Bercea, Beretta, Klausen, and Kozma [ESA'24] as a generalization of the online sorting problem, which was introduced by Aamand, Abrahamsen, Beretta, and Kleist [SODA'23] as a tool in their study of online geometric packing problems. Online metric TSP has been studied for a range of fixed metric spaces. For 1-dimensional Euclidean space, the problem is equivalent to online sorting, where an optimal competitive ratio of $Θ(\sqrt n)$ is known. For $d$-dimensional Euclidean space, the best-known upper bound is $O(2^{d} \sqrt{dn\log n})$, leaving a gap to the $Ω(\sqrt n)$ lower bound. Finally, for the uniform metric, where all distances are 0 or 1, the optimal competitive ratio is known to be $Θ(\log n)$. We study the problem for a general metric space, presenting an algorithm with competitive ratio $O(\sqrt n)$. In particular, we close the gap for $d$-dimensional Euclidean space, completely removing the dependence on dimension. One might hope to simultaneously guarantee competitive ratio $O(\sqrt n)$ in general and $O(\log n)$ for the uniform metric, but we show that this is impossible.