An MCP server that enables LLM agents to control a two-joint MuJoCo robot arm through tools for moving, reading state, and resetting. It deliberately omits inverse kinematics, so the agent must infer joint angles from observations.
Enables AI agents to interactively explore PDDL planning problems by exposing a PDDL engine as MCP tools for initialization, action execution, state inspection, and goal checking.
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.
A domain-agnostic MCP server for autonomous experimentation, generalizing Karpathy's autoresearch pattern into a reusable server that any AI agent can drive, pointed at any domain defined by a JSON configuration.
Enables AI agents to autonomously develop and test Godot 4 games through an MCP-based feedback loop, providing tools for authoring, running, observing, playtesting, and verifying game projects.
