Enables any AI agent to control a Pollen Robotics Microduck through MCP, including walking, sitting, picking objects, reading health, and stopping, with support for mock, simulated, or real hardware transports.
Enables agents to safely drive a simulated Franka Panda pick-and-place cell through MCP tools, with gated motion, emergency stop, structured errors, and audit logging.
An MCP server that gives AI agents full control and observability of the Webots robot simulator, enabling launch and monitoring of simulations, reinforcement learning training, model evaluation, and interactive scene manipulation.
Exposes MuJoCo physics simulation to AI assistants via 65 MCP tools, enabling natural language control of robotics simulation, trajectory optimization, contact analysis, and video export.
Provides physics simulation capabilities using PyBullet, enabling 3D physics world creation, object loading, force application, and state monitoring through MCP protocol.
