This paper outlines a system for machine improvisation with a human performer where the focus is limited to the provision of rhythmic complementarity. Complementarity is achieved through the real-time measurement of metrical coherence in currently playing rhythmic material that informs the generation of subsequent material. A robust computational approach building on recent theories of improvisational intelligence and situated cognition is described. This algorithm can be effective across a range of musical styles.