#!/usr/bin/env python3
"""
Example usage of SMILES Visualizer MCP Server
"""
import asyncio
import json
import base64
from pathlib import Path
# Example SMILES strings
EXAMPLE_SMILES = {
"ethanol": "CCO",
"ibuprofen": "CC(C)CC1=CC=C(C=C1)C(C)C(=O)O",
"caffeine": "CN1C=NC2=C1C(=O)N(C(=O)N2C)C",
"aspirin": "CC(=O)OC1=CC=CC=C1C(=O)O",
"biphenyl": "C1=CC=C(C=C1)C2=CC=CC=C2"
}
async def main():
"""Main example function"""
print("SMILES Visualizer MCP Server Example")
print("=" * 50)
print()
# This is a demonstration of how to use the MCP server
# In a real scenario, you would connect to the running server
print("Example SMILES strings:")
for name, smiles in EXAMPLE_SMILES.items():
print(f" {name}: {smiles}")
print()
print("Available tools:")
tools = [
"validate_smiles",
"get_molecular_info",
"visualize_rdkit",
"visualize_network",
"visualize_plotly",
"visualize_custom_matplotlib",
"compare_visualizations",
"batch_visualize"
]
for tool in tools:
print(f" - {tool}")
print()
print("Example usage patterns:")
print()
# Example 1: Validate SMILES
print("1. Validate SMILES:")
print(" await validate_smiles('CCO')")
print(" # Returns: {'valid': True, 'message': 'Valid SMILES', 'canonical_smiles': 'CCO'}")
print()
# Example 2: Get molecular information
print("2. Get molecular information:")
print(" await get_molecular_info('CCO')")
print(" # Returns molecular weight, atom count, properties, etc.")
print()
# Example 3: Create RDKit visualization
print("3. Create RDKit visualization:")
print(" await visualize_rdkit('CCO', size='400,300')")
print(" # Returns base64 encoded PNG image")
print()
# Example 4: Create network visualization
print("4. Create network visualization:")
print(" await visualize_network('CCO', layout='spring')")
print(" # Returns base64 encoded PNG image with network layout")
print()
# Example 5: Create interactive Plotly visualization
print("5. Create interactive Plotly visualization:")
print(" await visualize_plotly('CCO')")
print(" # Returns HTML content for interactive chart")
print()
# Example 6: Compare all visualizations
print("6. Compare all visualizations:")
print(" await compare_visualizations('CCO')")
print(" # Returns all visualization types and molecular info")
print()
# Example 7: Batch processing
print("7. Batch processing:")
print(" smiles_list = ['CCO', 'CC(C)CC1=CC=C(C=C1)C(C)C(=O)O', 'CN1C=NC2=C1C(=O)N(C(=O)N2C)C']")
print(" await batch_visualize(smiles_list, visualization_type='rdkit')")
print(" # Returns visualizations for all molecules")
print()
print("Integration with MCP clients:")
print()
print("The server can be integrated with any MCP-compatible client:")
print("- Claude Desktop")
print("- VS Code with MCP extension")
print("- Custom MCP clients")
print()
print("Client configuration example:")
print("""
{
"mcpServers": {
"smiles-visualizer": {
"command": "python",
"args": ["path/to/smiles_visualizer_mcp/server.py", "--host", "127.0.0.1", "--port", "8001"],
"env": {
"MCP_HOST": "127.0.0.1",
"MCP_PORT": "8001"
}
}
}
}
""")
print("Output formats:")
print("- Images: PNG format, base64 encoded")
print("- Interactive visualizations: HTML (Plotly)")
print("- Data: JSON format")
print()
print("Error handling:")
print("- Invalid SMILES strings return error messages")
print("- Missing dependencies are handled gracefully")
print("- All errors are returned as structured JSON")
print()
print("To run the server:")
print(" python server.py --host 127.0.0.1 --port 8001")
print()
print("To test the server:")
print(" python test_server.py")
print()
if __name__ == "__main__":
asyncio.run(main())
