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How to calibrate a scan and measure distances in it with Openreality

Give one known real distance, then have your assistant measure between points in the scene.

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

Who it is forA renovation planner, furniture shopper, or contractor who needs a reliable size check before buying or building.

The problemGuessing whether a couch fits against a wall or how far a counter sits from a window is error-prone, and 3D scans without scale give only relative numbers.

The outcomeMeasured distances and angles in metres, based on a calibration you supplied.

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. Pick a real distance you can verify with a tape measure, such as a counter edge to a window.
  4. Ask your assistant: "The counter edge to the window is 2.4 m. Calibrate the scene, then measure the couch."
  5. Ask for distances or angles between any other points you need checked.

Prompt for your agent

Using the openreality MCP tools on the scene <scene id>, calibrate with the known distance <distance in metres> between <point A> and <point B>, then measure <target measurement>. Verify that the result is reported in metres only after calibration succeeded, and flag it as relative otherwise.

Caveat. The calibration is only as accurate as the real distance you supply, and the README says server refusals and uncertainty labels are passed to the assistant unedited.

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