ComfyMCP Studio

Instructions

Args:
    theme: Overall theme for the tileset (e.g., "forest", "dungeon", "sci-fi")
    tile_types: List of tile types to generate (e.g., ["ground", "wall", "water"])
    preset: Style preset to use (default: tileset). Options: tileset, topdown_tile
    tile_size: Size of each tile in pixels (square)
    seed: Base seed for reproducibility (each tile gets seed+index)
    save_to_file: Whether to save images to disk

Returns:
    JSON with base64 images for each tile type

Implementation Reference

• server/main.py:302-379 (handler)

  The complete implementation of the generate_tileset tool handler, including registration via @mcp.tool() decorator. It generates multiple tile images based on theme and types using the AI backend, handles resizing, and returns JSON with base64 images.

  @mcp.tool()
  async def generate_tileset(
      theme: str,
      tile_types: List[str],
      preset: str = "tileset",
      tile_size: int = 32,
      seed: Optional[int] = None,
      save_to_file: bool = False
  ) -> str:
      """Generate a set of tileable game tiles.
      
      Args:
          theme: Overall theme for the tileset (e.g., "forest", "dungeon", "sci-fi")
          tile_types: List of tile types to generate (e.g., ["ground", "wall", "water"])
          preset: Style preset to use (default: tileset). Options: tileset, topdown_tile
          tile_size: Size of each tile in pixels (square)
          seed: Base seed for reproducibility (each tile gets seed+index)
          save_to_file: Whether to save images to disk
      
      Returns:
          JSON with base64 images for each tile type
      """
      if not tile_types:
          return json.dumps({"success": False, "error": "No tile_types provided"}, indent=2)
      
      preset_config = get_preset(preset)
      
      tiles = []
      for i, tile_type in enumerate(tile_types):
          prompt = f"{theme} {tile_type} tile"
          full_prompt = f"{preset_config.prompt_prefix}{prompt}{preset_config.prompt_suffix}"
          gen_seed = (seed + i) if seed is not None else None
   
          render_size = tile_size
          should_downscale = tile_size < min(preset_config.default_width, preset_config.default_height)
          if should_downscale:
              render_size = min(preset_config.default_width, preset_config.default_height)
           
          image_bytes = await backend.generate_image(
              prompt=full_prompt,
              negative_prompt=preset_config.negative_prompt,
              width=render_size,
              height=render_size,
              seed=gen_seed,
              steps=preset_config.steps,
              cfg_scale=preset_config.cfg_scale,
              sampler=preset_config.sampler,
              scheduler=preset_config.scheduler
          )
   
          if should_downscale:
              resample = Image.Resampling.NEAREST if preset.startswith("pixel") else Image.Resampling.LANCZOS
              image_bytes = resize_image(image_bytes, tile_size, tile_size, resample=resample)
          
          tile_data = {
              "index": i,
              "type": tile_type,
              "theme": theme,
              "image_base64": image_to_base64(image_bytes),
              "size": tile_size
          }
          
          if save_to_file:
              output_dir = ensure_directory(OUTPUT_DIR / "tiles" / theme)
              fname = generate_filename(prefix=f"tile_{tile_type}")
              file_path = output_dir / fname
              file_path.write_bytes(image_bytes)
              tile_data["file_path"] = str(file_path)
          
          tiles.append(tile_data)
      
      return json.dumps({
          "success": True,
          "theme": theme,
          "tile_size": tile_size,
          "count": len(tiles),
          "tiles": tiles
      }, indent=2)