ComfyMCP Studio

Instructions

Args:
    image_base64: Base64 encoded input image
    operations: List of operations to apply: "resize", "remove_background", "add_outline"
    resize_width: Target width for resize operation
    resize_height: Target height for resize operation
    outline_color: Hex color for outline (e.g., "#000000")
    outline_thickness: Thickness of outline in pixels
    save_to_file: Whether to save processed image to disk

Returns:
    JSON with processed image as base64

Implementation Reference

• server/main.py:816-868 (handler)

  The primary handler function for the 'process_image' tool. It decodes the input base64 image, applies the specified operations by calling helper functions (resize_image, remove_background, add_outline), encodes the result back to base64, and returns JSON. The @mcp.tool() decorator handles registration.

  @mcp.tool()
  async def process_image(
      image_base64: str,
      operations: List[str],
      resize_width: Optional[int] = None,
      resize_height: Optional[int] = None,
      outline_color: str = "#000000",
      outline_thickness: int = 1,
      save_to_file: bool = False
  ) -> str:
      """Apply post-processing operations to an image.
      
      Args:
          image_base64: Base64 encoded input image
          operations: List of operations to apply: "resize", "remove_background", "add_outline"
          resize_width: Target width for resize operation
          resize_height: Target height for resize operation
          outline_color: Hex color for outline (e.g., "#000000")
          outline_thickness: Thickness of outline in pixels
          save_to_file: Whether to save processed image to disk
      
      Returns:
          JSON with processed image as base64
      """
      import base64
      image_bytes = base64.b64decode(image_base64)
      
      for op in operations:
          if op == "resize" and resize_width and resize_height:
              image_bytes = resize_image(image_bytes, resize_width, resize_height)
          elif op == "remove_background":
              image_bytes = remove_background(image_bytes)
          elif op == "add_outline":
              # Parse hex color
              color = outline_color.lstrip("#")
              r, g, b = tuple(int(color[i:i+2], 16) for i in (0, 2, 4))
              image_bytes = add_outline(image_bytes, color=(r, g, b, 255), thickness=outline_thickness)
      
      result = {
          "success": True,
          "image_base64": image_to_base64(image_bytes),
          "operations_applied": operations
      }
      
      if save_to_file:
          output_dir = ensure_directory(OUTPUT_DIR / "processed")
          fname = generate_filename(prefix="processed")
          file_path = output_dir / fname
          file_path.write_bytes(image_bytes)
          result["file_path"] = str(file_path)
      
      return json.dumps(result, indent=2)

• server/utils.py:42-54 (helper)

  Helper function used by process_image for the 'resize' operation. Loads the image from bytes, resizes it using PIL, and returns new PNG bytes.

  def resize_image(
      image_bytes: bytes,
      width: int,
      height: int,
      resample: int = Image.Resampling.NEAREST
  ) -> bytes:
      """Resize an image to the specified dimensions."""
      img = Image.open(BytesIO(image_bytes))
      resized = img.resize((width, height), resample=resample)
      buffer = BytesIO()
      resized.save(buffer, format="PNG")
      return buffer.getvalue()

• server/utils.py:121-138 (helper)

  Helper function used by process_image for the 'remove_background' operation. Converts image to RGBA and sets near-white pixels to transparent.

  def remove_background(image_bytes: bytes, threshold: int = 10) -> bytes:
      """Simple background removal by making near-white pixels transparent."""
      img = Image.open(BytesIO(image_bytes)).convert("RGBA")
      data = img.getdata()
      
      new_data = []
      for item in data:
          # If pixel is close to white, make it transparent
          if item[0] > 255 - threshold and item[1] > 255 - threshold and item[2] > 255 - threshold:
              new_data.append((255, 255, 255, 0))
          else:
              new_data.append(item)
      
      img.putdata(new_data)
      buffer = BytesIO()
      img.save(buffer, format="PNG")
      return buffer.getvalue()

• server/utils.py:140-170 (helper)

  Helper function used by process_image for the 'add_outline' operation. Detects edges by checking transparent neighbors and adds colored outline pixels.

  def add_outline(
      image_bytes: bytes,
      color: Tuple[int, int, int, int] = (0, 0, 0, 255),
      thickness: int = 1
  ) -> bytes:
      """Add an outline around non-transparent pixels."""
      img = Image.open(BytesIO(image_bytes)).convert("RGBA")
      
      # Create outline image
      outline = Image.new("RGBA", img.size, (0, 0, 0, 0))
      
      pixels = img.load()
      outline_pixels = outline.load()
      
      for y in range(img.height):
          for x in range(img.width):
              if pixels[x, y][3] > 0:  # Non-transparent pixel
                  # Check neighbors
                  for dy in range(-thickness, thickness + 1):
                      for dx in range(-thickness, thickness + 1):
                          nx, ny = x + dx, y + dy
                          if 0 <= nx < img.width and 0 <= ny < img.height:
                              if pixels[nx, ny][3] == 0:  # Transparent neighbor
                                  outline_pixels[x, y] = color
                                  break
      
      # Composite outline under original
      result = Image.alpha_composite(outline, img)
      buffer = BytesIO()
      result.save(buffer, format="PNG")
      return buffer.getvalue()