Vascular shunt insertion is a common surgical procedure performed to restore blood flow to damaged tissues temporarily. It usually requires a surgeon and a surgical assistant. We consider three scenarios, (1) a surgeon is available locally; (2) a remote surgeon is available via teleoperation; (3) no surgeon is available. In each scenario, a minimally invasive surgical-assist da Vinci robot operates in a different mode either by teleoperation or automation. Robotic assistance for this procedure is challenging due to precision and control uncertainty. The role of the robot in this task depends on the availability of a human surgeon. We propose a trimodal framework for vascular shunt insertion assisted by a da Vinci Research Kit (dVRK) robotic surgical assistant (RSA). To help further study for the community, we also present a physics-based simulated environment for shunt insertion built on top of the NVIDIA Isaac ORBIT simulator. We collect a large dataset of trajectories for the shunt insertion environment using ORBIT and implement these trajectories to show the simulator’s realism, showcasing the possibility for future work to use the simulator for policy learning. Physical experiments demonstrate a success rate of 65%-100% for mode (1), 100% for mode (2), and 75%-95% for mode (3) across vessel phantoms with different sizes, color, and material properties.