ComfyMCP Studio

Instructions

Args:
    prompts: List of asset descriptions
    preset: Style preset to use for all generations
    width: Override width for all assets
    height: Override height for all assets
    seed: Base seed for reproducibility (each prompt gets seed+index)
    save_to_file: Whether to save all images to disk

Returns:
    JSON with all generated assets

Implementation Reference

• server/main.py:972-1042 (handler)

  The batch_generate tool handler: an async function decorated with @mcp.tool() that registers and implements the tool. It generates multiple game assets in batch from a list of prompts using the configured backend (Mock or ComfyUI), applies presets, handles parameters like width/height/seed, and returns JSON with base64 images or file paths.

  @mcp.tool()
  async def batch_generate(
      prompts: List[str],
      preset: str = "default",
      width: Optional[int] = None,
      height: Optional[int] = None,
      seed: Optional[int] = None,
      save_to_file: bool = False
  ) -> str:
      """Generate multiple assets in batch from a list of prompts.
      
      Args:
          prompts: List of asset descriptions
          preset: Style preset to use for all generations
          width: Override width for all assets
          height: Override height for all assets
          seed: Base seed for reproducibility (each prompt gets seed+index)
          save_to_file: Whether to save all images to disk
      
      Returns:
          JSON with all generated assets
      """
      if not prompts:
          return json.dumps({"success": False, "error": "No prompts provided"}, indent=2)
      
      preset_config = get_preset(preset)
      
      results = []
      for i, prompt in enumerate(prompts):
          full_prompt = f"{preset_config.prompt_prefix}{prompt}{preset_config.prompt_suffix}"
          
          img_width = width or preset_config.default_width
          img_height = height or preset_config.default_height
          gen_seed = (seed + i) if seed is not None else None
          
          image_bytes = await backend.generate_image(
              prompt=full_prompt,
              negative_prompt=preset_config.negative_prompt,
              width=img_width,
              height=img_height,
              seed=gen_seed,
              steps=preset_config.steps,
              cfg_scale=preset_config.cfg_scale,
              sampler=preset_config.sampler,
              scheduler=preset_config.scheduler
          )
          
          asset_data = {
              "index": i,
              "prompt": prompt,
              "image_base64": image_to_base64(image_bytes),
              "width": img_width,
              "height": img_height
          }
          
          if save_to_file:
              output_dir = ensure_directory(OUTPUT_DIR / "batch")
              fname = generate_filename(prefix=f"batch_{i}")
              file_path = output_dir / fname
              file_path.write_bytes(image_bytes)
              asset_data["file_path"] = str(file_path)
          
          results.append(asset_data)
      
      return json.dumps({
          "success": True,
          "preset": preset,
          "count": len(results),
          "assets": results
      }, indent=2)