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How to export a scan as robot-training data with Openreality

Turn a scanned space into a LeRobot or GR00T dataset, or an Isaac Sim or MuJoCo scene.

Credentials. The sign-in stores a revocable API key on your machine, so keep that key private.

Who it is forA robotics engineer or ML researcher who needs a realistic environment and dataset built from a real room.

The problemBuilding a simulation or training dataset for a real space by hand takes days of modeling and labeling.

The outcomeA downloadable zip of robot-training data, saved locally by the MCP process.

What you need first

  • Node.js and npx, so the openreality-mcp package can run
  • An MCP-capable AI assistant such as Claude Code, Codex, Cursor, or Claude desktop
  • A phone video of the space you want to scan
  • A browser to complete the one-time sign-in (hosted service)

Steps

  1. Add the tools with claude mcp add openreality -- npx -y openreality-mcp serve or the Codex equivalent.
  2. Sign in once with npx -y openreality-mcp login.
  3. Confirm the scan you want is reconstructed and, if you need metric dimensions, calibrated first.
  4. Ask: "Export this scan as robot-training data and save the zip locally."

Prompt for your agent

Using the openreality MCP tools, export the scene <scene id> as robot-training data in the <format: LeRobot, GR00T, Isaac Sim, or MuJoCo> format and save the zip to <local path>. Verify that the zip exists locally and that the export format matches your request.

Caveat. The README lists robot-training exports as a hosted service, so this use case depends on the hosted service rather than a self-hosted server.

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