first commit
This commit is contained in:
Matteo Benedetto
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# MCP Image Recognition Server Package
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from .server import mcp
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#!/usr/bin/env python3
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"""
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Post-installation script to automatically configure Kilocode MCP settings.
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"""
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import json
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import os
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import sys
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from pathlib import Path
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def get_kilocode_config_path():
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"""Find the Kilocode MCP settings file."""
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# Common paths for Kilocode/VSCodium
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possible_paths = [
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Path.home() / ".config/VSCodium/User/globalStorage/kilocode.kilo-code/settings/mcp_settings.json",
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Path.home() / ".config/Code/User/globalStorage/kilocode.kilo-code/settings/mcp_settings.json",
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Path.home() / "Library/Application Support/VSCodium/User/globalStorage/kilocode.kilo-code/settings/mcp_settings.json",
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Path.home() / "Library/Application Support/Code/User/globalStorage/kilocode.kilo-code/settings/mcp_settings.json",
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]
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for path in possible_paths:
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if path.exists():
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return path
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return None
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def add_to_kilocode_config():
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"""Add the image-recognition server to Kilocode's MCP settings."""
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config_path = get_kilocode_config_path()
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if not config_path:
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print("⚠️ Kilocode MCP settings file not found.")
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print(" You'll need to manually add the server configuration.")
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print("\n Add this to your MCP settings:")
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print(json.dumps({
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"image-recognition": {
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"command": "uvx",
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"args": ["image-recognition-mcp"],
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"env": {
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"OPENAI_API_KEY": "your-openai-api-key-here"
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}
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}
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}, indent=2))
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return False
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try:
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# Read existing config
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with open(config_path, 'r') as f:
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config = json.load(f)
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# Ensure mcpServers exists
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if "mcpServers" not in config:
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config["mcpServers"] = {}
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# Check if already configured
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if "image-recognition" in config["mcpServers"]:
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print("✅ Image Recognition MCP server already configured in Kilocode")
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return True
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# Add our server
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config["mcpServers"]["image-recognition"] = {
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"command": "uvx",
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"args": ["image-recognition-mcp"],
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"env": {
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"OPENAI_API_KEY": "your-openai-api-key-here"
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}
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}
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# Backup original config
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backup_path = config_path.with_suffix('.json.backup')
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with open(backup_path, 'w') as f:
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json.dump(config, f, indent=2)
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# Write updated config
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with open(config_path, 'w') as f:
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json.dump(config, f, indent=2)
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print("✅ Successfully added Image Recognition MCP server to Kilocode!")
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print(f" Config file: {config_path}")
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print(f" Backup saved: {backup_path}")
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print("\n⚠️ Remember to:")
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print(" 1. Replace 'your-openai-api-key-here' with your actual OpenAI API key")
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print(" 2. Restart Kilocode to load the new server")
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return True
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except Exception as e:
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print(f"❌ Error updating Kilocode config: {e}")
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return False
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def main():
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"""Main entry point for the installer."""
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print("🚀 Image Recognition MCP Server - Post-Install Configuration")
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print("=" * 60)
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if add_to_kilocode_config():
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print("\n✨ Installation complete!")
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else:
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print("\n⚠️ Manual configuration required.")
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print(" See PUBLISHING.md for instructions.")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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import base64
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import io
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import logging
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import os
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from typing import Optional
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from PIL import Image
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from fastmcp import FastMCP
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import openai
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# Configure logging
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logging.basicConfig(
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level=logging.DEBUG,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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filename='/home/enne2/Sviluppo/tetris-sdl/mcp-image-server/image_server.log'
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)
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logger = logging.getLogger(__name__)
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# Create FastMCP server instance
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mcp = FastMCP("ImageRecognitionServer")
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# Get OpenAI API key from environment
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OPENAI_API_KEY = os.getenv('OPENAI_API_KEY', '')
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HAS_OPENAI = bool(OPENAI_API_KEY and OPENAI_API_KEY != 'your-openai-api-key-here')
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if HAS_OPENAI:
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openai.api_key = OPENAI_API_KEY
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logger.info("OpenAI API key configured - AI descriptions enabled")
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else:
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logger.warning("No valid OpenAI API key - using basic image metadata only")
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@mcp.tool()
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def describe_image(image_data: str, mime_type: str = 'image/jpeg') -> str:
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"""
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Describe an image using base64 encoded image data
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Args:
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image_data: Base64 encoded image data
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mime_type: MIME type of the image (default: image/jpeg)
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Returns:
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Detailed description of the image
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"""
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try:
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logger.debug(f"Describing image - MIME type: {mime_type}")
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# Decode base64 image
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image_bytes = base64.b64decode(image_data)
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image = Image.open(io.BytesIO(image_bytes))
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# Log image details
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logger.info(f"Image size: {image.size}, mode: {image.mode}")
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# If OpenAI is available, use Vision API
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if HAS_OPENAI:
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try:
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response = openai.chat.completions.create(
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model="gpt-4o-mini",
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "Describe this image in detail, including objects, colors, composition, and any text visible."},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:{mime_type};base64,{image_data}"
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}
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}
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]
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}
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],
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max_tokens=500
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)
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description = response.choices[0].message.content
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logger.debug(f"OpenAI description: {description}")
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return description
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except Exception as e:
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logger.error(f"OpenAI API error: {str(e)}", exc_info=True)
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# Fall back to basic metadata
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return f"OpenAI API error: {str(e)}\n\nBasic metadata:\n- Size: {image.size[0]}x{image.size[1]} pixels\n- Mode: {image.mode}\n- Format: {image.format or 'Unknown'}"
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# Return basic metadata if no OpenAI
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description = f"Image Analysis (Basic Metadata):\n- Size: {image.size[0]}x{image.size[1]} pixels\n- Mode: {image.mode}\n- Format: {image.format or 'Unknown'}\n\nNote: For AI-powered descriptions, configure OPENAI_API_KEY in MCP settings."
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logger.debug(f"Returning basic description: {description}")
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return description
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except Exception as e:
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logger.error(f"Error describing image: {str(e)}", exc_info=True)
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return f"Error describing image: {str(e)}"
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@mcp.tool()
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def describe_image_from_file(file_path: str) -> str:
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"""
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Describe an image from a file path
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Args:
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file_path: Path to the image file
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Returns:
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Detailed description of the image
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"""
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try:
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logger.debug(f"Describing image from file: {file_path}")
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# Open the image file
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with open(file_path, 'rb') as image_file:
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# Encode image to base64
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image_data = base64.b64encode(image_file.read()).decode('utf-8')
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# Determine MIME type from file extension
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mime_type = 'image/jpeg'
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if file_path.lower().endswith('.png'):
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mime_type = 'image/png'
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elif file_path.lower().endswith('.gif'):
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mime_type = 'image/gif'
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elif file_path.lower().endswith('.webp'):
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mime_type = 'image/webp'
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# Use the describe_image function
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return describe_image(image_data, mime_type)
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except Exception as e:
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logger.error(f"Error reading image file: {str(e)}", exc_info=True)
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return f"Error reading image file: {str(e)}"
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def main():
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"""Main entry point for the MCP server."""
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logger.info("Starting MCP Image Recognition Server")
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mcp.run()
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if __name__ == "__main__":
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main()
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