#!/usr/bin/env python3
"""
MCP Simulation Test - Tier 3 Test Suite

Tests MCP tool interface, server simulation, and real-world query scenarios.
Ensures the MCP layer works correctly as clients would experience it.
"""
import os
import sys
import time
import json
import asyncio
from pathlib import Path
from typing import Dict, Any, Tuple, List, Optional
from concurrent.futures import ThreadPoolExecutor
import importlib.util

# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent / "src"))

from tests.support.api_client import DuneTestClient, TestQueryManager
from tests.support.helpers import PerformanceTimer, TestResultCollector, MCPToolSimulator, TestEnvironment
from tests.support import QueryFactory, ExpectedResults, TestDataGenerator

def load_env_variables():
    """Load environment variables from .env file."""
    env_file = Path(__file__).parent.parent.parent / ".env"
    if env_file.exists():
        with open(env_file) as f:
            for line in f:
                line = line.strip()
                if line and not line.startswith("#") and "=" in line:
                    key, value = line.split("=", 1)
                    os.environ[key] = value

def test_mcp_server_simulation() -> Tuple[bool, Dict[str, Any]]:
    """Simulate MCP server startup and tool discovery."""
    print("🖥️ Testing MCP Server Simulation...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Load the MCP server components
        sys.path.insert(0, str(Path(__file__).parent.parent.parent / "src"))
        
        # Import configuration and tool classes
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        print("   ✓ Successfully imported MCP components")
        
        # Simulate server configuration
        api_key = os.getenv("DUNE_API_KEY")
        if not api_key:
            return False, {"error": "DUNE_API_KEY required for MCP simulation"}
        
        print(f"   ✓ API key configured: {api_key[:8]}...")
        
        # Initialize server configuration
        config = Config(dune=DuneConfig(api_key=api_key))
        timer.checkpoint("config_initialized")
        
        # Initialize services
        query_service = QueryService(config)
        timer.checkpoint("query_service_initialized")
        
        # Initialize query history
        from pathlib import Path as PathObj
        history_path = PathObj("/tmp") / "mcp_simulation_history.jsonl"
        artifact_root = PathObj("/tmp") / "mcp_simulation_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        timer.checkpoint("query_history_initialized")
        
        # Initialize tools
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        timer.checkpoint("tools_initialized")
        
        # Simulate tool discovery
        tools = {
            "execute_query": execute_tool
        }
        
        print(f"   ✓ Initialized {len(tools)} tools")
        
        # Validate tool schemas
        schema_validations = {}
        for tool_name, tool_instance in tools.items():
            schema_validation = MCPToolSimulator.validate_tool_schema(tool_instance)
            schema_validations[tool_name] = schema_validation
            
            if schema_validation['valid']:
                print(f"   ✓ {tool_name} schema valid")
            else:
                print(f"   ✗ {tool_name} schema invalid: {schema_validation['errors']}")
        
        timer.checkpoint("schemas_validated")
        
        # Check server health
        server_health = {
            "components_loaded": True,
            "tools_available": len(tools),
            "schemas_valid": all(v['valid'] for v in schema_validations.values()),
            "api_configured": bool(config.dune.api_key),
            "services_initialized": len([query_service, query_history])
        }
        
        health_score = sum([
            server_health["components_loaded"],
            server_health["tools_available"] > 0,
            server_health["schemas_valid"],
            server_health["api_configured"],
            server_health["services_initialized"] >= 2
        ]) / 5
        
        timer.stop()
        
        details = {
            "server_health": server_health,
            "health_score": health_score,
            "schema_validations": schema_validations,
            "tools_available": list(tools.keys()),
            "timings": timer.get_report()
        }
        
        return health_score >= 0.8, details
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_mcp_tool_parameter_validation() -> Tuple[bool, Dict[str, Any]]:
    """Test MCP tool parameter validation and schema compliance."""
    print("🔧 Testing MCP Tool Parameter Validation...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "param_validation_history.jsonl"
        artifact_root = PathObj("/tmp") / "param_validation_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Get tool schema
        schema = execute_tool.get_parameter_schema()
        timer.checkpoint("schema_retrieved")
        
        print(f"   ✓ Retrieved tool schema: {schema.get('type', 'unknown')}")
        
        # Test various parameter combinations
        parameter_test_cases = [
            {
                "name": "minimal_valid_params",
                "parameters": {"query": "SELECT 1 as test"},
                "should_pass": True
            },
            {
                "name": "full_valid_params", 
                "parameters": {
                    "query": "SELECT 1 as test, 'hello' as message",
                    "parameters": {"test": "value"},
                    "performance": "medium",
                    "limit": 10,
                    "format": "json"
                },
                "should_pass": True
            },
            {
                "name": "missing_required_query",
                "parameters": {"limit": 10},
                "should_pass": False
            },
            {
                "name": "invalid_performance",
                "parameters": {
                    "query": "SELECT 1",
                    "performance": "invalid"
                },
                "should_pass": False
            },
            {
                "name": "invalid_format",
                "parameters": {
                    "query": "SELECT 1",
                    "format": "invalid"
                },
                "should_pass": False
            },
            {
                "name": "negative_limit",
                "parameters": {
                    "query": "SELECT 1",
                    "limit": -1
                },
                "should_pass": False
            }
        ]
        
        validation_results = []
        
        for test_case in parameter_test_cases:
            test_name = test_case["name"]
            parameters = test_case["parameters"]
            should_pass = test_case["should_pass"]
            
            print(f"   Testing {test_name}...")
            
            # Simulate parameter validation by calling the tool
            try:
                result = MCPToolSimulator.simulate_tool_call(execute_tool, parameters)
                
                validation_passed = (
                    (should_pass and result['success']) or 
                    (not should_pass and not result['success'])
                )
                
                validation_results.append({
                    "test_name": test_name,
                    "parameters": parameters,
                    "should_pass": should_pass,
                    "actual_success": result['success'],
                    "validation_passed": validation_passed,
                    "result": result
                })
                
                status = "✓" if validation_passed else "✗"
                print(f"   {status} {test_name}: {'passed' if validation_passed else 'failed'}")
                
            except Exception as e:
                # Handle exception for parameter validation
                if not should_pass:
                    validation_results.append({
                        "test_name": test_name,
                        "parameters": parameters,
                        "should_pass": should_pass,
                        "validation_passed": True,
                        "error": str(e)
                    })
                    print(f"   ✓ {test_name}: correctly rejected with exception")
                else:
                    validation_results.append({
                        "test_name": test_name,
                        "parameters": parameters,
                        "should_pass": should_pass,
                        "validation_passed": False,
                        "error": str(e)
                    })
                    print(f"   ✗ {test_name}: unexpected rejection with exception: {e}")
        
        timer.checkpoint("parameter_tests_completed")
        
        # Analyze results
        passed_validations = sum(1 for r in validation_results if r['validation_passed'])
        total_validations = len(validation_results)
        validation_rate = passed_validations / total_validations
        
        timer.stop()
        
        print(f"   Parameter validation: {passed_validations}/{total_validations} passed")
        
        details = {
            "tool_schema": schema,
            "validation_results": validation_results,
            "passed_validations": passed_validations,
            "total_validations": total_validations,
            "validation_rate": validation_rate,
            "timings": timer.get_report()
        }
        
        return validation_rate >= 0.8, details
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_mcp_request_response_cycle() -> Tuple[bool, Dict[str, Any]]:
    """Test request/response cycle as MCP client would see it."""
    print("🔄 Testing MCP Request/Response Cycle...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "request_response_history.jsonl"
        artifact_root = PathObj("/tmp") / "request_response_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Test request/response scenarios
        request_scenarios = [
            {
                "name": "simple_query_request",
                "request": {
                    "query": "SELECT 1 as test_col, 'hello' as message",
                    "limit": 5
                },
                "expected_response_keys": ["ok", "error"]
            },
            {
                "name": "parameterized_query_request",
                "request": {
                    "query": "SELECT {{test_param}} as value, 42 as constant",
                    "parameters": {"test_param": "hello_world"},
                    "limit": 10
                },
                "expected_response_keys": ["ok", "error"]
            },
            {
                "name": "performance_level_request",
                "request": {
                    "query": QueryFactory.aggregate_query(),
                    "performance": "medium",
                    "limit": 1
                },
                "expected_response_keys": ["ok", "error"]
            }
        ]
        
        response_validations = []
        
        for scenario in request_scenarios:
            scenario_name = scenario["name"]
            request = scenario["request"]
            expected_keys = scenario["expected_response_keys"]
            
            print(f"   Testing {scenario_name}...")
            
            try:
                # Simulate MCP request
                response_result = MCPToolSimulator.simulate_tool_call(execute_tool, request)
                
                # Validate response structure
                if response_result['success']:
                    response_data = response_result['data']
                    
                    # Check expected keys exist
                    missing_keys = [key for key in expected_keys if key not in response_data]
                    
                    response_validations.append({
                        "scenario_name": scenario_name,
                        "request": request,
                        "response_success": response_result['success'],
                        "response_data": response_data,
                        "missing_keys": missing_keys,
                        "validation_passed": len(missing_keys) == 0,
                        "result": response_result
                    })
                    
                    print(f"   ✓ {scenario_name}: response structure valid")
                    
                    # Show snippet of response
                    if 'preview' in response_data:
                        preview = response_data['preview']
                        print(f"     Preview: {preview.get('rowcount', 'unknown')} rows")
                    
                else:
                    response_validations.append({
                        "scenario_name": scenario_name,
                        "request": request,
                        "response_success": False,
                        "error": response_result.get('error', 'Unknown error'),
                        "validation_passed": False  # Failed response is validation failure for these test cases
                    })
                    
                    print(f"   ✗ {scenario_name}: request failed - {response_result.get('error', 'Unknown')}")
                    
            except Exception as e:
                response_validations.append({
                    "scenario_name": scenario_name,
                    "request": request,
                    "response_success": False,
                    "error": str(e),
                    "validation_passed": False,
                    "exception": True
                })
                
                print(f"   ✗ {scenario_name}: exception - {e}")
        
        timer.checkpoint("request_response_tests_completed")
        
        # Analyze results
        successful_responses = sum(1 for r in response_validations if r['validation_passed'])
        total_responses = len(response_validations)
        success_rate = successful_responses / total_responses
        
        timer.stop()
        
        print(f"   Request/Response cycle: {successful_responses}/{total_responses} successful")
        
        details = {
            "response_validations": response_validations,
            "successful_responses": successful_responses,
            "total_responses": total_responses,
            "success_rate": success_rate,
            "timings": timer.get_report()
        }
        
        return success_rate >= 0.7, details  # Allow some leeway for API variability
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_real_world_query_scenarios() -> Tuple[bool, Dict[str, Any]]:
    """Test real-world query scenarios that would be used in production."""
    print("🌍 Testing Real-World Query Scenarios...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "real_world_history.jsonl"
        artifact_root = PathObj("/tmp") / "real_world_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Real-world query scenarios
        real_world_scenarios = [
            {
                "name": "analytics_dashboard_query",
                "description": "Typical analytics dashboard query with aggregations",
                "request": {
                    "query": """
                    SELECT 
                        DATE_TRUNC('day', created_at) as date,
                        COUNT(*) as total_users,
                        SUM(CASE WHEN active THEN 1 ELSE 0 END) as active_users,
                        AVG(session_duration) as avg_session
                    FROM user_activity 
                    WHERE created_at >= '2024-01-01'
                    GROUP BY date
                    ORDER BY date DESC
                    LIMIT 30
                    """,
                    "performance": "medium",
                    "limit": 5
                },
                "expected_structure": ["date", "total", "active", "duration"]
            },
            {
                "name": "financial_summary_query",
                "description": "Financial summary with multiple calculations",
                "request": {
                    "query": """
                    SELECT 
                        SUM(amount) as total_revenue,
                        AVG(amount) as avg_transaction,
                        COUNT(*) as transaction_count,
                        MIN(amount) as min_amount,
                        MAX(amount) as max_amount
                    FROM (
                        SELECT 100 + (n * 10) as amount
                        FROM generate_series(1, 100) as n
                    ) transactions
                    """,
                    "performance": "medium",
                    "limit": 1
                },
                "expected_structure": ["revenue", "avg", "count", "min", "max"]
            },
            {
                "name": "time_series_analysis",
                "description": "Time series analysis for trend identification",
                "request": {
                    "query": """
                    SELECT 
                        DATE_TRUNC('week', event_date) as week,
                        category,
                        COUNT(*) as events,
                        SUM(value) as total_value
                    FROM (
                        SELECT 
                            DATE '2024-01-01' + INTERVAL '1 day' * n as event_date,
                            CASE WHEN n % 3 = 0 THEN 'A' WHEN n % 3 = 1 THEN 'B' ELSE 'C' END as category,
                            n * 5 as value
                        FROM generate_series(1, 30) as n
                    ) event_data
                    GROUP BY week, category
                    ORDER BY week DESC, category
                    LIMIT 10
                    """,
                    "performance": "medium",
                    "limit": 10
                },
                "expected_structure": ["week", "category", "events", "value"]
            }
        ]
        
        scenario_results = []
        
        for scenario in real_world_scenarios:
            scenario_name = scenario["name"]
            description = scenario["description"]
            request = scenario["request"]
            expected_structure = scenario["expected_structure"]
            
            print(f"   Testing {scenario_name}: {description}")
            
            try:
                # Execute real-world query scenario
                result = MCPToolSimulator.simulate_tool_call(execute_tool, request)
                
                if result['success']:
                    response_data = result['data']
                    
                    # Validate response structure
                    structure_validation = True
                    if 'preview' in response_data:
                        columns = response_data['preview'].get('columns', [])
                        # Check if expected structure keywords are present
                        missing_structure = [
                            keyword for keyword in expected_structure 
                            if not any(keyword.lower() in col.lower() for col in columns)
                        ]
                        structure_validation = len(missing_structure) == 0
                        
                        if missing_structure:
                            print(f"     ⚠ Missing expected structure: {missing_structure}")
                    
                    scenario_results.append({
                        "scenario_name": scenario_name,
                        "description": description,
                        "request": request,
                        "success": result['success'],
                        "response_data": response_data,
                        "structure_validation": structure_validation,
                        "validation_passed": structure_validation,
                        "result": result
                    })
                    
                    status = "✓" if structure_validation else "⚠"
                    print(f"   {status} {scenario_name}: structure {'validated' if structure_validation else 'needs review'}")
                    
                    # Show preview
                    if 'preview' in response_data:
                        preview = response_data['preview']
                        print(f"     Result: {preview.get('rowcount', 'unknown')} rows, {len(preview.get('columns', []))} columns")
                    
                else:
                    scenario_results.append({
                        "scenario_name": scenario_name,
                        "description": description,
                        "request": request,
                        "success": False,
                        "error": result.get('error', 'Unknown error'),
                        "validation_passed": False
                    })
                    
                    print(f"   ✗ {scenario_name}: failed - {result.get('error', 'Unknown')}")
                    
            except Exception as e:
                scenario_results.append({
                    "scenario_name": scenario_name,
                    "description": description,
                    "request": request,
                    "success": False,
                    "error": str(e),
                    "validation_passed": False,
                    "exception": True
                })
                
                print(f"   ✗ {scenario_name}: exception - {e}")
        
        timer.checkpoint("real_world_scenarios_completed")
        
        # Analyze results
        successful_scenarios = sum(1 for r in scenario_results if r.get('validation_passed', False))
        total_scenarios = len(scenario_results)
        success_rate = successful_scenarios / total_scenarios
        
        timer.stop()
        
        print(f"   Real-world scenarios: {successful_scenarios}/{total_scenarios} successful")
        
        details = {
            "scenario_results": scenario_results,
            "successful_scenarios": successful_scenarios,
            "total_scenarios": total_scenarios,
            "success_rate": success_rate,
            "timings": timer.get_report()
        }
        
        return success_rate >= 0.6, details  # Allow flexibility for real-world variability
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_mcp_error_handling() -> Tuple[bool, Dict[str, Any]]:
    """Test error handling through the MCP interface."""
    print("⚠️ Testing MCP Error Handling...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "error_handling_history.jsonl"
        artifact_root = PathObj("/tmp") / "error_handling_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Error scenarios to test
        error_scenarios = [
            {
                "name": "invalid_sql_syntax",
                "request": {
                    "query": "SELECTTTT INVALID SQL SYNTAX"
                },
                "expected_error_type": "sql_syntax"
            },
            {
                "name": "missing_required_parameters",
                "request": {
                    "query": "SELECT {{missing_param}} as value"
                },
                "expected_error_type": "missing_parameter"
            },
            {
                "name": "empty_query",
                "request": {
                    "query": ""
                },
                "expected_error_type": "empty_query"
            },
            {
                "name": "invalid_parameter_values",
                "request": {
                    "query": "SELECT 1 as test",
                    "limit": "invalid_number"
                },
                "expected_error_type": "invalid_parameter"
            },
            {
                "name": "timeout_simulation",
                "request": {
                    "query": "SELECT 1",  # This should work, but we'll test error response format
                    "timeout_seconds": 0.001  # Very short timeout to force error
                },
                "expected_error_type": "timeout"
            }
        ]
        
        error_handling_results = []
        
        for scenario in error_scenarios:
            scenario_name = scenario["name"]
            request = scenario["request"]
            expected_error_type = scenario["expected_error_type"]
            
            print(f"   Testing {scenario_name}...")
            
            try:
                # Simulate error scenario
                result = MCPToolSimulator.simulate_tool_call(execute_tool, request)
                
                if result['success']:
                    # Unexpected success - this might be valid for some error scenarios
                    error_handling_results.append({
                        "scenario_name": scenario_name,
                        "request": request,
                        "expected_error_type": expected_error_type,
                        "actual_success": True,
                        "error_handling_passed": False,  # Expected error but got success
                        "reason": "Expected error but got success",
                        "result": result
                    })
                    
                    print(f"   ⚠ {scenario_name}: got success instead of expected error")
                    
                else:
                    # Expected failure - check error format
                    error_info = result.get('error', 'Unknown error')
                    error_type = result.get('error_type', 'Unknown')
                    
                    # Validate error information
                    has_error_info = bool(error_info)
                    has_error_type = bool(error_type)
                    
                    error_handling_passed = has_error_info and has_error_type
                    
                    error_handling_results.append({
                        "scenario_name": scenario_name,
                        "request": request,
                        "expected_error_type": expected_error_type,
                        "actual_success": False,
                        "actual_error_type": error_type,
                        "error_info": error_info,
                        "error_handling_passed": error_handling_passed,
                        "result": result
                    })
                    
                    status = "✓" if error_handling_passed else "⚠"
                    print(f"   {status} {scenario_name}: {error_type} - {error_info[:100]}...")
                    
            except Exception as e:
                # Exception in error handling is not ideal but acceptable
                error_handling_results.append({
                    "scenario_name": scenario_name,
                    "request": request,
                    "expected_error_type": expected_error_type,
                    "actual_success": False,
                    "exception": str(e),
                    "error_handling_passed": True,  # Exception indicates error was caught
                    "result": "exception"
                })
                
                print(f"   ✓ {scenario_name}: exception caught - {str(e)[:100]}...")
        
        timer.checkpoint("error_scenarios_completed")
        
        # Analyze error handling results
        proper_error_handling = sum(1 for r in error_handling_results if r['error_handling_passed'])
        total_scenarios = len(error_handling_results)
        error_handling_rate = proper_error_handling / total_scenarios
        
        timer.stop()
        
        print(f"   Error handling: {proper_error_handling}/{total_scenarios} handled correctly")
        
        details = {
            "error_handling_results": error_handling_results,
            "proper_error_handling": proper_error_handling,
            "total_scenarios": total_scenarios,
            "error_handling_rate": error_handling_rate,
            "timings": timer.get_report()
        }
        
        return error_handling_rate >= 0.8, details
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_concurrent_mcp_usage() -> Tuple[bool, Dict[str, Any]]:
    """Test concurrent MCP tool usage scenarios."""
    print("🚀 Testing Concurrent MCP Usage...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "concurrent_mcp_history.jsonl"
        artifact_root = PathObj("/tmp") / "concurrent_mcp_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Test concurrent usage scenarios
        concurrent_scenarios = [
            {
                "name": "simple_concurrent_queries",
                "concurrent_requests": [
                    {"query": f"SELECT {i} as query_id, 'concurrent {i}' as description", "limit": 5}
                    for i in range(3)
                ]
            },
            {
                "name": "mixed_concurrent_queries",
                "concurrent_requests": [
                    {"query": "SELECT 1 as simple", "performance": "low"},
                    {"query": "SELECT 2 as medium, 3 as value", "performance": "medium"},
                    {"query": "SELECT SUM(n) as total FROM generate_series(1, 10) as n", "performance": "medium"}
                ]
            }
        ]
        
        concurrent_results = []
        
        for scenario in concurrent_scenarios:
            scenario_name = scenario["name"]
            requests = scenario["concurrent_requests"]
            
            print(f"   Testing {scenario_name} with {len(requests)} concurrent requests...")
            
            try:
                # Execute requests concurrently
                def execute_single_request(request_data, index):
                    """Execute a single MCP request."""
                    return MCPToolSimulator.simulate_tool_call(execute_tool, request_data), index
                
                with ThreadPoolExecutor(max_workers=len(requests)) as executor:
                    futures = [
                        executor.submit(execute_single_request, req, i)
                        for i, req in enumerate(requests)
                    ]
                    
                    # Collect results
                    scenario_results = []
                    for future in futures:
                        try:
                            result, index = future.result(timeout=120)  # 2 minute timeout
                            scenario_results.append({
                                "index": index,
                                "result": result,
                                "success": result.get('success', False)
                            })
                        except Exception as e:
                            scenario_results.append({
                                "index": index,
                                "result": {"success": False, "error": str(e)},
                                "success": False,
                                "exception": True
                            })
                
                # Analyze concurrent execution
                successful_requests = [r for r in scenario_results if r['success']]
                failed_requests = [r for r in scenario_results if not r['success']]
                
                concurrent_results.append({
                    "scenario_name": scenario_name,
                    "total_requests": len(requests),
                    "successful_requests": len(successful_requests),
                    "failed_requests": len(failed_requests),
                    "success_rate": len(successful_requests) / len(requests),
                    "results": scenario_results
                })
                
                print(f"   ✓ {scenario_name}: {len(successful_requests)}/{len(requests)} successful")
                
            except Exception as e:
                concurrent_results.append({
                    "scenario_name": scenario_name,
                    "total_requests": len(requests),
                    "successful_requests": 0,
                    "failed_requests": len(requests),
                    "success_rate": 0.0,
                    "error": str(e)
                })
                
                print(f"   ✗ {scenario_name}: failed - {e}")
        
        timer.checkpoint("concurrent_scenarios_completed")
        
        # Analyze overall concurrent usage
        total_concurrent_requests = sum(r['total_requests'] for r in concurrent_results)
        total_successful_requests = sum(r['successful_requests'] for r in concurrent_results)
        overall_success_rate = total_successful_requests / total_concurrent_requests if total_concurrent_requests > 0 else 0
        
        timer.stop()
        
        print(f"   Concurrent usage: {total_successful_requests}/{total_concurrent_requests} requests successful")
        
        details = {
            "concurrent_results": concurrent_results,
            "total_concurrent_requests": total_concurrent_requests,
            "total_successful_requests": total_successful_requests,
            "overall_success_rate": overall_success_rate,
            "timings": timer.get_report()
        }
        
        return overall_success_rate >= 0.7, details  # 70% success rate for concurrent scenarios
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def test_mcp_performance_characterization() -> Tuple[bool, Dict[str, Any]]:
    """Test performance characterization of MCP tool layer."""
    print("📊 Testing MCP Performance Characterization...")
    timer = PerformanceTimer()
    
    try:
        timer.start()
        
        # Import MCP components
        from spice_mcp.config import Config, DuneConfig
        from spice_mcp.mcp.tools.execute_query import ExecuteQueryTool
        from spice_mcp.service_layer.query_service import QueryService
        from spice_mcp.logging.query_history import QueryHistory
        
        from pathlib import Path as PathObj
        
        api_key = os.getenv("DUNE_API_KEY")
        config = Config(dune=DuneConfig(api_key=api_key))
        
        # Initialize services
        query_service = QueryService(config)
        history_path = PathObj("/tmp") / "performance_history.jsonl"
        artifact_root = PathObj("/tmp") / "performance_artifacts"
        query_history = QueryHistory(history_path, artifact_root)
        
        # Initialize tool
        execute_tool = ExecuteQueryTool(config, query_service, query_history)
        
        # Performance test scenarios
        performance_scenarios = [
            {
                "name": "tool_initialization",
                "test_function": lambda: ExecuteQueryTool(config, query_service, query_history),
                "expected_max_time": 5.0,
                "iterations": 5
            },
            {
                "name": "schema_retrieval",
                "test_function": lambda: execute_tool.get_parameter_schema(),
                "expected_max_time": 1.0,
                "iterations": 10
            },
            {
                "name": "simple_query_execution",
                "test_function": lambda: MCPToolSimulator.simulate_tool_call(
                    execute_tool, 
                    {"query": "SELECT 1 as test_col", "limit": 1}
                ),
                "expected_max_time": 20.0,
                "iterations": 3
            },
            {
                "name": "parameterized_query_execution",
                "test_function": lambda: MCPToolSimulator.simulate_tool_call(
                    execute_tool,
                    {
                        "query": "SELECT {{param}} as value",
                        "parameters": {"param": "test_value"},
                        "limit": 1
                    }
                ),
                "expected_max_time": 25.0,
                "iterations": 3
            }
        ]
        
        performance_results = []
        
        for scenario in performance_scenarios:
            scenario_name = scenario["name"]
            test_function = scenario["test_function"]
            expected_max_time = scenario["expected_max_time"]
            iterations = scenario["iterations"]
            
            print(f"   Testing {scenario_name} ({iterations} iterations)...")
            
            execution_times = []
            successes = 0
            
            for i in range(iterations):
                iteration_timer = PerformanceTimer()
                iteration_timer.start()
                
                try:
                    result = test_function()
                    iteration_timer.stop()
                    
                    # For query executions, check success
                    if isinstance(result, dict):
                        if 'success' in result:
                            success = result['success']
                        else:
                            # Tool initialization, schema retrieval usually succeed
                            success = True
                    else:
                        # Tool objects
                        success = True
                    
                    execution_times.append(iteration_timer.duration)
                    if success:
                        successes += 1
                        
                    status = "✓" if success else "✗"
                    print(f"     {status} Iteration {i+1}: {iteration_timer.duration:.3f}s")
                    
                except Exception as e:
                    iteration_timer.stop()
                    execution_times.append(iteration_timer.duration)
                    print(f"     ✗ Iteration {i+1}: exception - {str(e)[:50]}...")
            
            # Calculate scenario statistics
            if execution_times:
                avg_time = sum(execution_times) / len(execution_times)
                min_time = min(execution_times)
                max_time = max(execution_times)
                time_variance = max_time - min_time
                
                scenario_performance = {
                    "scenario_name": scenario_name,
                    "iterations": iterations,
                    "execution_times": execution_times,
                    "avg_time": avg_time,
                    "min_time": min_time,
                    "max_time": max_time,
                    "time_variance": time_variance,
                    "successes": successes,
                    "success_rate": successes / iterations,
                    "within_expected_time": avg_time <= expected_max_time
                }
                
                performance_results.append(scenario_performance)
                
                time_status = "✓" if scenario_performance['within_expected_time'] else "⚠"
                print(f"   {time_status} {scenario_name}: avg {avg_time:.3f}s (expected ≤{expected_max_time}s)")
        
        timer.checkpoint("performance_tests_completed")
        
        # Analyze overall performance
        performance_summary = {
            "total_scenarios": len(performance_results),
            "scenarios_within_expected_time": sum(1 for r in performance_results if r['within_expected_time']),
            "overall_success_rate": sum(r['success_rate'] for r in performance_results) / len(performance_results) if performance_results else 0
        }
        
        performance_ok = (
            performance_summary['scenarios_within_expected_time'] >= performance_summary['total_scenarios'] * 0.75
            and performance_summary['overall_success_rate'] >= 0.8
        )
        
        timer.stop()
        
        print(f"   Performance summary: {performance_summary['scenarios_within_expected_time']}/{performance_summary['total_scenarios']} scenarios within expected time")
        print(f"   Overall success rate: {performance_summary['overall_success_rate']:.1%}")
        
        details = {
            "performance_results": performance_results,
            "performance_summary": performance_summary,
            "performance_ok": performance_ok,
            "timings": timer.get_report()
        }
        
        return performance_ok, details
        
    except Exception as e:
        timer.stop()
        return False, {"error": str(e), "timings": timer.get_report()}

def main():
    """Run MCP simulation test suite."""
    print("🖥️ DUNE MCP SIMULATION TEST SUITE")
    print("=" * 50)
    
    # Load environment
    load_env_variables()
    
    # Check API key
    if not os.getenv("DUNE_API_KEY"):
        print("❌ DUNE_API_KEY not found. Please set it in your environment or .env file.")
        return False
    
    # Initialize result collector
    results = TestResultCollector()
    results.start_collection()
    
    # Run MCP simulation tests
    tests = [
        ("MCP Server Simulation", test_mcp_server_simulation),
        ("MCP Tool Parameter Validation", test_mcp_tool_parameter_validation),
        ("MCP Request/Response Cycle", test_mcp_request_response_cycle),
        ("Real-World Query Scenarios", test_real_world_query_scenarios),
        ("MCP Error Handling", test_mcp_error_handling),
        ("Concurrent MCP Usage", test_concurrent_mcp_usage),
        ("MCP Performance Characterization", test_mcp_performance_characterization),
    ]
    
    passed = 0
    total = len(tests)
    
    for test_name, test_func in tests:
        print(f"\n{'-' * 40}")
        try:
            success, details = test_func()
            results.add_result(test_name, success, details)
            
            if success:
                print(f"✅ {test_name} PASSED")
                passed += 1
            else:
                error = details.get('error', 'Unknown error')
                print(f"❌ {test_name} FAILED: {error}")
                
        except Exception as e:
            results.add_result(test_name, False, {"error": str(e)})
            print(f"❌ {test_name} EXCEPTION: {e}")
    
    results.finish_collection()
    summary = results.get_summary()
    
    # Summary
    print(f"\n{'=' * 50}")
    print("🎯 MCP SIMULATION TEST SUMMARY")
    print(f"✅ {passed}/{total} tests passed")
    print(f"⏱️ Total duration: {summary['duration']:.2f}s")
    
    if passed >= total * 0.8:  # 80% pass rate for simulation tests
        print("🎉 MCP simulation tests passed! Interface is ready for client usage.")
        return True
    else:
        print("⚠️ Some MCP simulation tests failed. Review interface issues.")
        return False

if __name__ == "__main__":
    success = main()
    sys.exit(0 if success else 1)
