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Run structured, auditable LeRobot workflows, dataset conversions, and CLI operations.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "lerobot-mcp" yet — see the docs or source repo.
List the available LeRobot CLI workflows, built-in examples, and common use cases, organized by training, evaluation, and data processing stages.
A structured list of available commands, example contents, and the stage where each is used.
Convert an existing robot demonstration dataset into a LeRobot-compatible format, and explain the required fields, conversion steps, and output directory structure.
A dataset conversion plan with field mapping, execution steps, and the target directory layout.
Check whether the current LeRobot dataset and workflow configuration are complete, and identify missing items, format issues, and risks to training reproducibility.
An auditable review listing issues, risk levels, and recommended fixes.
Connect ROBOT.md to MCP agents for structured manifest access and validation.
Connect LLMs to ROS robots for command-driven interaction and automation.
Connect MCP-compatible AI assistants to a Robonine robot arm for local control.
Connect LLMs with ROS robots for intelligent control and automation.
Control lab automation devices via MCP and test workflows in simulation.
Build, debug, and manage software tasks with natural language across LLMs.