LumenX-MCP Legal Spend Intelligence Server

#!/usr/bin/env python3 """ Basic usage example for Legal Spend MCP Server This example demonstrates how to interact with the Legal Spend MCP Server using a Python client. """ import asyncio import json from datetime import date, timedelta from typing import Dict, Any import os from dotenv import load_dotenv # For this example, we'll simulate MCP client calls # In production, you would use an actual MCP client library async def call_mcp_tool(tool_name: str, **params) -> Dict[str, Any]: """Simulate calling an MCP tool""" print(f"\n📞 Calling tool: {tool_name}") print(f" Parameters: {json.dumps(params, indent=2)}") # In a real implementation, this would call the MCP server # For demo purposes, we'll return sample data if tool_name == "get_legal_spend_summary": return { "period": f"{params['start_date']} to {params['end_date']}", "total_amount": 250000.0, "currency": "USD", "record_count": 45, "top_vendors": [ {"name": "Smith & Associates", "amount": 85000.0}, {"name": "Jones Legal", "amount": 65000.0}, {"name": "Brown Law Firm", "amount": 45000.0} ], "by_department": { "Legal": 180000.0, "Compliance": 50000.0, "Finance": 20000.0 } } elif tool_name == "search_legal_transactions": return [ { "transaction_id": "INV-2024-001", "date": "2024-01-15", "vendor_name": "Smith & Associates", "matter_name": "ABC Corp Acquisition", "amount": 25000.0, "currency": "USD", "description": "Due diligence services" }, { "transaction_id": "INV-2024-002", "date": "2024-01-20", "vendor_name": "Smith & Associates", "matter_name": "ABC Corp Acquisition", "amount": 15000.0, "currency": "USD", "description": "Contract negotiation" } ] return {"error": "Unknown tool"} async def main(): """Main example function""" print("=" * 60) print("Legal Spend MCP Server - Basic Usage Example") print("=" * 60) # Load environment variables load_dotenv() # Example 1: Get spend summary for the current quarter print("\n📊 Example 1: Quarterly Spend Summary") print("-" * 40) # Calculate current quarter dates today = date.today() quarter_start = date(today.year, ((today.month - 1) // 3) * 3 + 1, 1) quarter_end = date(today.year, ((today.month - 1) // 3 + 1) * 3 + 1, 1) - timedelta(days=1) summary = await call_mcp_tool( "get_legal_spend_summary", start_date=quarter_start.isoformat(), end_date=quarter_end.isoformat() ) print(f"\n✅ Total Legal Spend: ${summary['total_amount']:,.2f} {summary['currency']}") print(f" Transaction Count: {summary['record_count']}") print("\n Top Vendors:") for vendor in summary['top_vendors'][:3]: print(f" - {vendor['name']}: ${vendor['amount']:,.2f}") # Example 2: Search for specific vendor transactions print("\n🔍 Example 2: Search Vendor Transactions") print("-" * 40) transactions = await call_mcp_tool( "search_legal_transactions", search_term="Smith & Associates", start_date="2024-01-01", end_date="2024-12-31", min_amount=10000.0 ) print(f"\n✅ Found {len(transactions)} transactions") for txn in transactions[:3]: print(f"\n Invoice: {txn['transaction_id']}") print(f" Date: {txn['date']}") print(f" Matter: {txn['matter_name']}") print(f" Amount: ${txn['amount']:,.2f}") print(f" Description: {txn['description']}") # Example 3: Department budget analysis print("\n💰 Example 3: Department Budget Analysis") print("-" * 40) budget_analysis = await call_mcp_tool( "get_budget_vs_actual", department="Legal", start_date="2024-01-01", end_date="2024-03-31", budget_amount=200000.0 ) # Simulated response budget_analysis = { "department": "Legal", "budget_analysis": { "budget_amount": 200000.0, "actual_spend": 180000.0, "variance": -20000.0, "variance_percentage": -10.0, "status": "under_budget" }, "recommendations": [ "Current spending is within acceptable variance", "Continue monitoring for any unusual patterns" ] } print(f"\n✅ Budget Status: {budget_analysis['budget_analysis']['status'].replace('_', ' ').title()}") print(f" Budget: ${budget_analysis['budget_analysis']['budget_amount']:,.2f}") print(f" Actual: ${budget_analysis['budget_analysis']['actual_spend']:,.2f}") print(f" Variance: ${budget_analysis['budget_analysis']['variance']:,.2f} " f"({budget_analysis['budget_analysis']['variance_percentage']:.1f}%)") print("\n Recommendations:") for rec in budget_analysis['recommendations']: print(f" • {rec}") # Example 4: Vendor performance analysis print("\n📈 Example 4: Vendor Performance Analysis") print("-" * 40) vendor_performance = await call_mcp_tool( "get_vendor_performance", vendor_name="Smith & Associates", start_date="2024-01-01", end_date="2024-06-30", include_benchmarks=True ) # Simulated response vendor_performance = { "vendor_name": "Smith & Associates", "performance_metrics": { "total_spend": 150000.0, "invoice_count": 12, "average_invoice_amount": 12500.0 }, "spend_trend": { "trend": "stable", "change_percentage": 2.5 }, "industry_benchmarks": { "average_invoice_benchmark": 15000.0, "cost_efficiency_score": 0.92 } } print(f"\n✅ Vendor: {vendor_performance['vendor_name']}") print(f" Total Spend: ${vendor_performance['performance_metrics']['total_spend']:,.2f}") print(f" Invoice Count: {vendor_performance['performance_metrics']['invoice_count']}") print(f" Average Invoice: ${vendor_performance['performance_metrics']['average_invoice_amount']:,.2f}") print(f" Spend Trend: {vendor_performance['spend_trend']['trend'].title()} " f"({vendor_performance['spend_trend']['change_percentage']:+.1f}%)") if 'industry_benchmarks' in vendor_performance: print(f"\n Benchmarks:") print(f" - Industry Avg Invoice: ${vendor_performance['industry_benchmarks']['average_invoice_benchmark']:,.2f}") print(f" - Cost Efficiency Score: {vendor_performance['industry_benchmarks']['cost_efficiency_score']:.2f}") print("\n" + "=" * 60) print("✨ Example completed successfully!") print("=" * 60) if __name__ == "__main__": # Run the example asyncio.run(main())