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opslon

BlenderMCP

by opslon

import_generated_asset

Import 3D assets generated by Hyper3D Rodin into Blender scenes using task UUID or request ID parameters to complete modeling workflows.

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
task_uuidNo
request_idNo

Implementation Reference

  • The implementation of the import_generated_asset tool, which acts as a handler for importing assets into Blender via an MCP tool registration.
    @mcp.tool()
    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)}"
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the tool imports an asset and returns success status, but lacks details on permissions, error handling, rate limits, or what 'imported successfully' entails (e.g., file location, format). This is inadequate for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by parameter details and a key usage rule. Every sentence adds value without redundancy, and it is appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description covers basic purpose, parameters, and usage context. However, as a mutation tool, it lacks details on behavioral traits (e.g., side effects, error cases) and output specifics, leaving gaps in completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the purpose of each parameter ('name of the object in scene', 'task_uuid for MAIN_SITE mode', 'request_id for FAL_AI mode') and adds critical guidance to 'Only give one of {task_uuid, request_id} based on the Hyper3D Rodin Mode!' This significantly clarifies parameter usage beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Import') and resource ('asset generated by Hyper3D Rodin'), specifying it occurs 'after the generation task is completed.' It distinguishes from siblings like 'import_generated_asset_hunyuan' by focusing on Hyper3D Rodin, but could be more explicit about the distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context for when to use ('after the generation task is completed') and specifies parameter usage based on Hyper3D Rodin Mode (MAIN_SITE vs. FAL_AI). However, it does not explicitly state when NOT to use it or compare with alternatives like 'import_generated_asset_hunyuan'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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