#!/usr/bin/env python3 """ Simple MCP Client Example for OpenProblems Spatial Transcriptomics This example demonstrates how to connect to and interact with the OpenProblems Spatial Transcriptomics MCP Server. """ import asyncio import json import subprocess import sys from pathlib import Path from mcp import ClientSession, StdioServerParameters from mcp.client.stdio import stdio_client async def demo_mcp_interaction(): """Demonstrate basic interactions with the MCP server.""" print("๐Ÿš€ Starting OpenProblems Spatial Transcriptomics MCP Client Demo") print("=" * 60) # Configure server parameters server_params = StdioServerParameters( command="python", args=["-m", "mcp_server.main"], env=None, ) try: # Connect to the MCP server async with stdio_client(server_params) as (read, write): async with ClientSession(read, write) as session: print("โœ… Connected to MCP server") # Initialize the session await session.initialize() print("โœ… Session initialized") # List available resources print("\n๐Ÿ“š Available Resources:") print("-" * 30) resources = await session.list_resources() for resource in resources: print(f" โ€ข {resource.name}: {resource.description}") # List available tools print("\n๐Ÿ› ๏ธ Available Tools:") print("-" * 30) tools = await session.list_tools() for tool in tools: print(f" โ€ข {tool.name}: {tool.description}") # Test echo tool print("\n๐Ÿ”„ Testing Echo Tool:") print("-" * 30) echo_result = await session.call_tool( "echo_test", arguments={"message": "Hello from MCP client!"} ) print(f"Echo response: {echo_result}") # Read server status print("\n๐Ÿ“Š Server Status:") print("-" * 30) try: status_content = await session.read_resource("server://status") status_data = json.loads(status_content) print(f"Server Name: {status_data['server_name']}") print(f"Version: {status_data['version']}") print(f"Status: {status_data['status']}") print("Capabilities:") for capability, enabled in status_data['capabilities'].items(): status_icon = "โœ…" if enabled else "โŒ" print(f" {status_icon} {capability}") except Exception as e: print(f"Error reading server status: {e}") # Read documentation examples print("\n๐Ÿ“– Sample Documentation:") print("-" * 30) try: nextflow_docs = await session.read_resource("documentation://nextflow") docs_data = json.loads(nextflow_docs) print("Nextflow Best Practices:") for practice, description in docs_data['best_practices'].items(): print(f" โ€ข {practice}: {description}") except Exception as e: print(f"Error reading documentation: {e}") # List available tools using the MCP tool print("\n๐Ÿ” Detailed Tool Information:") print("-" * 30) try: tools_result = await session.call_tool("list_available_tools", arguments={}) tools_data = json.loads(tools_result) for tool in tools_data: print(f" โ€ข {tool['name']}") print(f" Description: {tool['description']}") required_params = tool.get('required_params', []) if required_params: print(f" Required params: {', '.join(required_params)}") print() except Exception as e: print(f"Error listing tools: {e}") # Read pipeline templates print("\n๐Ÿงฌ Spatial Transcriptomics Pipeline Templates:") print("-" * 30) try: templates_content = await session.read_resource("templates://spatial-workflows") templates_data = json.loads(templates_content) for template_id, template_info in templates_data.items(): print(f" โ€ข {template_info['name']}") print(f" Description: {template_info['description']}") print(f" Inputs: {', '.join(template_info['inputs'])}") print(f" Outputs: {', '.join(template_info['outputs'])}") print() except Exception as e: print(f"Error reading templates: {e}") print("โœ… Demo completed successfully!") except Exception as e: print(f"โŒ Error during demo: {e}") return False return True async def demo_workflow_execution(): """Demonstrate workflow execution capabilities (if tools are available).""" print("\n๐Ÿงช Workflow Execution Demo") print("=" * 60) # Check if required tools are available required_tools = ["nextflow", "docker"] missing_tools = [] for tool in required_tools: try: result = subprocess.run([tool, "--version"], capture_output=True, text=True, timeout=10) if result.returncode == 0: print(f"โœ… {tool} is available") else: missing_tools.append(tool) except (subprocess.TimeoutExpired, FileNotFoundError): missing_tools.append(tool) if missing_tools: print(f"โš ๏ธ Missing tools: {', '.join(missing_tools)}") print(" Workflow execution demo skipped") return # Configure server parameters server_params = StdioServerParameters( command="python", args=["-m", "mcp_server.main"], env=None, ) try: async with stdio_client(server_params) as (read, write): async with ClientSession(read, write) as session: await session.initialize() # Example: Analyze a mock Nextflow log print("\n๐Ÿ“‹ Testing Log Analysis:") print("-" * 30) # Create a mock log file for testing mock_log_path = Path("/tmp/test_nextflow.log") mock_log_content = """ N E X T F L O W ~ version 23.04.0 Launching `main.nf` [abc123] DSL2 - revision: def456 executor > local (2) [12/abc123] process > PROCESS_1 [100%] 1 of 1 โœ“ [34/def456] process > PROCESS_2 [ 0%] 0 of 1, failed: 1 ERROR ~ Error executing process > 'PROCESS_2' Caused by: Process `PROCESS_2` terminated with an error exit status (137) Command executed: python script.py --input data.h5ad Command exit status: 137 Execution failed """ try: with open(mock_log_path, 'w') as f: f.write(mock_log_content) # Analyze the log using MCP log_analysis = await session.call_tool( "analyze_nextflow_log", arguments={"log_file_path": str(mock_log_path)} ) analysis_data = json.loads(log_analysis) print(f"Log analysis completed:") print(f" File size: {analysis_data['file_size']} bytes") print(f" Execution status: {analysis_data['execution_status']}") if analysis_data['issues_found']: print(" Issues found:") for issue in analysis_data['issues_found']: print(f" โ€ข {issue['issue']}: {issue['suggestion']}") # Clean up mock_log_path.unlink(missing_ok=True) except Exception as e: print(f"Error in log analysis demo: {e}") mock_log_path.unlink(missing_ok=True) except Exception as e: print(f"โŒ Error during workflow demo: {e}") async def main(): """Main function to run the demo.""" print("๐Ÿงฌ OpenProblems Spatial Transcriptomics MCP Client") print(" Model Context Protocol Demo") print(" Version 0.1.0") print() # Run basic interaction demo success = await demo_mcp_interaction() if success: # Run workflow execution demo await demo_workflow_execution() print("\n" + "=" * 60) print("Demo completed! ๐ŸŽ‰") print("\nTo use this MCP server with AI agents:") print("1. Start the server: python -m mcp_server.main") print("2. Configure your AI agent to connect via stdio transport") print("3. Use the available tools and resources for spatial transcriptomics workflows") if __name__ == "__main__": # Check if the server module is available try: import mcp_server.main except ImportError: print("โŒ MCP server module not found. Make sure you're in the project directory") print(" and have installed the package: pip install -e .") sys.exit(1) # Run the demo asyncio.run(main())