generate_hyper3d_model_via_images
Create 3D models with materials from images and import them into Blender for 3D scene integration and scaling adjustments.
Instructions
Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender. The 3D asset has built-in materials. The generated model has a normalized size, so re-scaling after generation can be useful.
Parameters:
input_image_paths: The absolute paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode.
input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode.
bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model.
Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode. Returns a message indicating success or failure.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input_image_paths | No | ||
| input_image_urls | No | ||
| bbox_condition | No |
Implementation Reference
- src/blender_mcp/server.py:742-796 (handler)The handler function decorated with @mcp.tool(), implementing the tool logic: validates input images (paths or URLs), processes bbox_condition, encodes images if paths provided, sends 'create_rodin_job' command to Blender connection, and returns job details or error.@mcp.tool() def generate_hyper3d_model_via_images( ctx: Context, input_image_paths: list[str]=None, input_image_urls: list[str]=None, bbox_condition: list[float]=None ) -> str: """ Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender. The 3D asset has built-in materials. The generated model has a normalized size, so re-scaling after generation can be useful. Parameters: - input_image_paths: The **absolute** paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode. - input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode. - bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model. Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode. Returns a message indicating success or failure. """ if input_image_paths is not None and input_image_urls is not None: return f"Error: Conflict parameters given!" if input_image_paths is None and input_image_urls is None: return f"Error: No image given!" if input_image_paths is not None: if not all(os.path.exists(i) for i in input_image_paths): return "Error: not all image paths are valid!" images = [] for path in input_image_paths: with open(path, "rb") as f: images.append( (Path(path).suffix, base64.b64encode(f.read()).decode("ascii")) ) elif input_image_urls is not None: if not all(urlparse(i) for i in input_image_paths): return "Error: not all image URLs are valid!" images = input_image_urls.copy() try: blender = get_blender_connection() result = blender.send_command("create_rodin_job", { "text_prompt": None, "images": images, "bbox_condition": _process_bbox(bbox_condition), }) succeed = result.get("submit_time", False) if succeed: return json.dumps({ "task_uuid": result["uuid"], "subscription_key": result["jobs"]["subscription_key"], }) else: return json.dumps(result) except Exception as e: logger.error(f"Error generating Hyper3D task: {str(e)}") return f"Error generating Hyper3D task: {str(e)}"