BlenderMCP

Instructions

Implementation Reference

• src/blender_mcp/server.py:747-801 (handler)

  The @mcp.tool()-decorated handler function that implements the core logic for generating a Hyper3D model from images. It validates inputs, encodes images if from paths, sends a 'create_rodin_job' command to Blender via socket, and returns task 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)}"

• src/blender_mcp/server.py:702-709 (helper)

  Helper function used by the tool to process and normalize the bbox_condition parameter into a list of integers scaled to 0-100.

  def _process_bbox(original_bbox: list[float] | list[int] | None) -> list[int] | None:
      if original_bbox is None:
          return None
      if all(isinstance(i, int) for i in original_bbox):
          return original_bbox
      if any(i<=0 for i in original_bbox):
          raise ValueError("Incorrect number range: bbox must be bigger than zero!")
      return [int(float(i) / max(original_bbox) * 100) for i in original_bbox] if original_bbox else None

• src/blender_mcp/server.py:754-765 (schema)

  The docstring within the handler provides the input schema/validation details and usage instructions for the tool parameters.

  """
  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.

• src/blender_mcp/server.py:747-747 (registration)

  The @mcp.tool() decorator registers this function as an MCP tool.

  @mcp.tool()