Add MCP

app.py

@@ -84,6 +84,17 @@ def _calculate_new_dimensions_wan(pil_image, mod_val, calculation_max_area,
     return new_h, new_w
 
 def handle_image_upload_for_dims_wan(uploaded_pil_image, current_h_val, current_w_val):
+    """
+    Handle image upload and calculate appropriate dimensions for video generation.
+    
+    Args:
+        uploaded_pil_image: The uploaded image (PIL Image or numpy array)
+        current_h_val: Current height slider value
+        current_w_val: Current width slider value
+        
+    Returns:
+        Tuple of gr.update objects for height and width sliders
+    """
     if uploaded_pil_image is None:
         return gr.update(value=DEFAULT_H_SLIDER_VALUE), gr.update(value=DEFAULT_W_SLIDER_VALUE)
     try:
@@ -137,7 +148,24 @@ def generate_video(
     seed=42,
     progress=gr.Progress(track_tqdm=True)
 ):
-    """The main function to generate video, called by the Gradio interface."""
+    """
+    Generate a video from text prompt and optional image using the Wan 2.2 TI2V model.
+    
+    Args:
+        image: Optional input image (numpy array) for image-to-video generation
+        prompt: Text prompt describing the desired video
+        height: Target video height in pixels
+        width: Target video width in pixels
+        duration_seconds: Desired video duration in seconds
+        sampling_steps: Number of denoising steps for video generation
+        guide_scale: Guidance scale for classifier-free guidance
+        shift: Sample shift parameter for the model
+        seed: Random seed for reproducibility (-1 for random)
+        progress: Gradio progress tracker
+        
+    Returns:
+        Path to the generated video file
+    """
     if seed == -1:
         seed = random.randint(0, sys.maxsize)
 
@@ -250,4 +278,4 @@ with gr.Blocks(css=css, theme=gr.themes.Soft(), delete_cache=(60, 900)) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(mcp_server=True)