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#!/usr/bin/env python3
"""
A1D MCP Server with Gradio - Official MCP Implementation
Following Gradio's official MCP documentation
"""
import gradio as gr
import os
from utils import A1DAPIClient, prepare_request_data, format_response_with_preview
from config import TOOLS_CONFIG
def get_api_client():
"""Get API client with current API key"""
api_key = os.getenv("A1D_API_KEY")
if not api_key:
raise ValueError("A1D_API_KEY environment variable is required")
return A1DAPIClient(api_key)
def remove_background(image_url: str) -> str:
"""
Remove background from images using AI.
Args:
image_url (str): The URL of the image to remove background from. Must be a valid HTTP/HTTPS URL pointing to an image file.
Returns:
str: A message indicating the result and the URL of the processed image.
"""
try:
if not image_url or not image_url.strip():
return "❌ Error: Please provide an image URL"
client = get_api_client()
data = prepare_request_data("remove_bg", image_url=image_url)
response = client.make_request_with_result(
TOOLS_CONFIG["remove_bg"]["api_endpoint"],
data,
timeout=120
)
message, media_url = format_response_with_preview(response, "remove_bg")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
def upscale_image(image_url: str, scale: str = "2") -> str:
"""
Upscale images using AI.
Args:
image_url (str): The URL of the image to upscale. Must be a valid HTTP/HTTPS URL pointing to an image file.
scale (str): Scale factor for upscaling. Choose from "2", "4", "8", or "16". Higher values produce larger images but take longer to process.
Returns:
str: A message indicating the result and the URL of the processed image.
"""
try:
if not image_url or not image_url.strip():
return "❌ Error: Please provide an image URL"
client = get_api_client()
data = prepare_request_data("image_upscaler", image_url=image_url, scale=int(scale))
response = client.make_request_with_result(
TOOLS_CONFIG["image_upscaler"]["api_endpoint"],
data,
timeout=120
)
message, media_url = format_response_with_preview(response, "image_upscaler")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
def generate_image(prompt: str) -> str:
"""
Generate images using AI from text prompts.
Args:
prompt (str): Text description of the image to generate. Be descriptive and specific for better results. Example: "A beautiful sunset over mountains with vibrant orange and purple colors".
Returns:
str: A message indicating the result and the URL of the generated image.
"""
try:
if not prompt or not prompt.strip():
return "❌ Error: Please provide a text prompt"
client = get_api_client()
data = prepare_request_data("image_generator", prompt=prompt)
response = client.make_request_with_result(
TOOLS_CONFIG["image_generator"]["api_endpoint"],
data,
timeout=120
)
message, media_url = format_response_with_preview(response, "image_generator")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
def vectorize_image(image_url: str) -> str:
"""
Convert images to vector format using AI.
Args:
image_url (str): The URL of the image to convert to vector format. Must be a valid HTTP/HTTPS URL pointing to an image file.
Returns:
str: A message indicating the result and the URL of the vectorized image.
"""
try:
if not image_url or not image_url.strip():
return "❌ Error: Please provide an image URL"
client = get_api_client()
data = prepare_request_data("image_vectorization", image_url=image_url)
response = client.make_request_with_result(
TOOLS_CONFIG["image_vectorization"]["api_endpoint"],
data,
timeout=120
)
message, media_url = format_response_with_preview(response, "image_vectorization")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
def extend_image(image_url: str) -> str:
"""
Extend images using AI.
Args:
image_url (str): The URL of the image to extend. Must be a valid HTTP/HTTPS URL pointing to an image file.
Returns:
str: A message indicating the result and the URL of the extended image.
"""
try:
if not image_url or not image_url.strip():
return "❌ Error: Please provide an image URL"
client = get_api_client()
data = prepare_request_data("image_extends", image_url=image_url)
response = client.make_request_with_result(
TOOLS_CONFIG["image_extends"]["api_endpoint"],
data,
timeout=120
)
message, media_url = format_response_with_preview(response, "image_extends")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
def upscale_video(video_url: str) -> str:
"""
Upscale videos using AI.
Args:
video_url (str): The URL of the video to upscale. Must be a valid HTTP/HTTPS URL pointing to a video file (MP4, AVI, MOV, etc.).
Returns:
str: A message indicating the result and the URL of the upscaled video.
"""
try:
if not video_url or not video_url.strip():
return "❌ Error: Please provide a video URL"
client = get_api_client()
data = prepare_request_data("video_upscaler", video_url=video_url)
response = client.make_request_with_result(
TOOLS_CONFIG["video_upscaler"]["api_endpoint"],
data,
timeout=300
)
message, media_url = format_response_with_preview(response, "video_upscaler")
return f"{message}\n\nResult URL: {media_url}" if media_url else message
except Exception as e:
return f"❌ Error: {str(e)}"
# Create the Gradio interface using the official MCP approach
demo = gr.Interface(
fn=remove_background,
inputs=[gr.Textbox(label="Image URL", placeholder="https://example.com/image.jpg", value="https://asset2.qieman.com/user-avatar/20240721/1071394_e15eb706-485d-4604-ad28-ac9830de1fe4.jpg")],
outputs=[gr.Textbox(label="Result")],
title="🤖 A1D MCP Server - Universal AI Tools",
description="Powerful AI image and video processing tools for any MCP-compatible client.",
examples=[
["https://asset2.qieman.com/user-avatar/20240721/1071394_e15eb706-485d-4604-ad28-ac9830de1fe4.jpg"],
["https://images.unsplash.com/photo-1506905925346-21bda4d32df4"]
]
)
if __name__ == "__main__":
# Check for API key
if not os.getenv("A1D_API_KEY"):
print("❌ Error: A1D_API_KEY environment variable is required")
print("Please set your API key in the Space settings")
exit(1)
print("🚀 Starting A1D MCP Server (Official Implementation)...")
print("✅ API key found")
print("🌐 MCP Server will be available at: /gradio_api/mcp/sse")
# Launch with MCP server enabled (official method)
demo.launch(
server_name="0.0.0.0",
server_port=7860,
share=False,
mcp_server=True # This is the official way to enable MCP
)
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