Environment assistant

The environment assistant builds and edits the world your robots live in. You describe the scene, for example “a workbench with an SO-101, a camera above it and two bins”, and it finds the right twins in the catalog, places them and proposes the changes for you to accept. When nothing in the catalog fits, it can generate a new asset.

What it does

You ask for	The assistant
A scene or a change to it	Searches the catalog first, places twins, and uses simple procedural primitives for basic geometry
An object the catalog doesn’t have	Generates a private URDF asset in the background while you keep editing (Generate assets)
A change to a generated asset	Builds a new candidate revision; the current asset stays unchanged until you accept the preview
Help with a reference	Takes tagged scene objects and reference images alongside your message

Generated assets start private and scoped to the environment that asked for them. Sharing them further follows the normal asset visibility controls.

Use it in the editor

Open an environment and select Agent in the right-hand panel.
Describe what you want. Tag scene objects or attach a reference image if it helps.
Review what the assistant proposes, then accept it.

The conversation stays the same when you switch between Edit and Monitor in Simulate or Live, within the same page session. Unsent drafts, tagged objects and reference images are kept when you visit Control and come back. In Monitor, action cards are read-only, and switching to Monitor asks the assistant to stop unfinished edits without stopping running robots or training jobs. To act on the robots themselves, use the control agent; it has its own composer. More on the editor: Environment editor.

Use it from Python

from cyberwave import Cyberwave

cw = Cyberwave()

# Create a new environment from a description
env = cw.agents.environment.create("A workbench with an SO-101 arm, a camera above it and two bins")

# Continue the conversation in an existing environment
reply = cw.agents.environment.message(environment_uuid, "Add a second camera on the left side")

# Models that can run the assistant
print(cw.agents.environment.models())

message() also accepts the conversation history, a pending_confirmation to answer, and an image (image_base64, image_mime_type) as a reference.

From your AI tools (MCP)

With the MCP server, Claude Code, Cursor or any MCP client can plan a scene with cw_plan_scene and create environments with cw_create_environment. cw_plan_scene is advisory: it returns a plan and checks, and changes nothing.

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What it does

Use it in the editor

Use it from Python

From your AI tools (MCP)

Next steps

Control agent

Generate assets with the assistant

​What it does

​Use it in the editor

​Use it from Python

​From your AI tools (MCP)

​Next steps

Control agent

Generate assets with the assistant

What it does

Use it in the editor

Use it from Python

From your AI tools (MCP)

Next steps