Skip to main content
Glama

import_generated_asset

Import AI-generated 3D models from Hyper3D Rodin into Blender scenes by providing the task UUID or request ID and object name.

Instructions

Import the asset generated by Hyper3D Rodin after the generation task is completed.

Parameters:

  • name: The name of the object in scene

  • task_uuid: For Hyper3D Rodin mode MAIN_SITE: The task_uuid given in the generate model step.

  • request_id: For Hyper3D Rodin mode FAL_AI: The request_id given in the generate model step.

Only give one of {task_uuid, request_id} based on the Hyper3D Rodin Mode! Return if the asset has been imported successfully.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
request_idNo
task_uuidNo

Implementation Reference

  • MCP tool handler function for 'import_generated_asset'. It is registered via @mcp.tool() decorator and proxies the import command to the Blender addon via the connection's send_command method. The function signature and docstring define the input schema.
    def import_generated_asset( ctx: Context, name: str, task_uuid: str=None, request_id: str=None, ): """ Import the asset generated by Hyper3D Rodin after the generation task is completed. Parameters: - name: The name of the object in scene - task_uuid: For Hyper3D Rodin mode MAIN_SITE: The task_uuid given in the generate model step. - request_id: For Hyper3D Rodin mode FAL_AI: The request_id given in the generate model step. Only give one of {task_uuid, request_id} based on the Hyper3D Rodin Mode! Return if the asset has been imported successfully. """ try: blender = get_blender_connection() kwargs = { "name": name } if task_uuid: kwargs["task_uuid"] = task_uuid elif request_id: kwargs["request_id"] = request_id result = blender.send_command("import_generated_asset", kwargs) return result except Exception as e: logger.error(f"Error generating Hyper3D task: {str(e)}") return f"Error generating Hyper3D task: {str(e)}"

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/spranjal3301/final-year-project'

If you have feedback or need assistance with the MCP directory API, please join our Discord server