/**
 * MCP Server Integration with Neural Trader
 *
 * Demonstrates using @neural-trader/mcp for:
 * - Model Context Protocol server setup
 * - 87+ trading tools exposed via JSON-RPC 2.0
 * - Claude Code integration
 * - Real-time trading operations
 *
 * This enables AI assistants to interact with the trading system
 */

// MCP Protocol configuration
const mcpConfig = {
  server: {
    name: 'neural-trader-mcp',
    version: '2.1.0',
    description: 'Neural Trader MCP Server - AI-powered trading tools'
  },

  // Transport settings
  transport: {
    type: 'stdio',          // stdio, http, or websocket
    port: 3000              // For HTTP/WebSocket
  },

  // Security settings
  security: {
    requireAuth: true,
    allowedOrigins: ['claude-code', 'claude-desktop'],
    rateLimits: {
      requestsPerMinute: 100,
      requestsPerHour: 1000
    }
  }
};

// Available MCP tools (87+)
const mcpTools = {
  // Market Data Tools
  marketData: [
    'getQuote',
    'getHistoricalData',
    'getOrderBook',
    'streamPrices',
    'getMarketStatus',
    'getExchangeInfo',
    'getCryptoPrice',
    'getForexRate'
  ],

  // Trading Tools
  trading: [
    'placeOrder',
    'cancelOrder',
    'modifyOrder',
    'getPositions',
    'getOrders',
    'getAccountBalance',
    'closePosition',
    'closeAllPositions'
  ],

  // Analysis Tools
  analysis: [
    'calculateIndicator',
    'runBacktest',
    'analyzeStrategy',
    'detectPatterns',
    'getCorrelation',
    'calculateVolatility',
    'getSeasonality',
    'performRegression'
  ],

  // Risk Management Tools
  risk: [
    'calculateVaR',
    'getMaxDrawdown',
    'calculateSharpe',
    'getPositionRisk',
    'checkRiskLimits',
    'runStressTest',
    'getGreeks',
    'calculateBeta'
  ],

  // Portfolio Tools
  portfolio: [
    'getPortfolioSummary',
    'optimizePortfolio',
    'rebalancePortfolio',
    'getPerformance',
    'getAllocation',
    'analyzeRiskContribution',
    'calculateCorrelationMatrix',
    'runMonteCarloSim'
  ],

  // Neural Network Tools
  neural: [
    'trainModel',
    'predict',
    'loadModel',
    'saveModel',
    'evaluateModel',
    'getModelInfo',
    'optimizeHyperparams',
    'runEnsemble'
  ],

  // Accounting Tools
  accounting: [
    'calculateCostBasis',
    'generateTaxReport',
    'trackGainsLosses',
    'exportTransactions',
    'reconcileAccounts',
    'calculateROI'
  ],

  // Utility Tools
  utilities: [
    'convertCurrency',
    'formatNumber',
    'parseTimeframe',
    'validateSymbol',
    'getTimezone',
    'scheduleTask'
  ]
};

async function main() {
  console.log('='.repeat(70));
  console.log('MCP Server Integration - Neural Trader');
  console.log('='.repeat(70));
  console.log();

  // 1. Server information
  console.log('1. MCP Server Configuration:');
  console.log('-'.repeat(70));
  console.log(`   Name:        ${mcpConfig.server.name}`);
  console.log(`   Version:     ${mcpConfig.server.version}`);
  console.log(`   Transport:   ${mcpConfig.transport.type}`);
  console.log(`   Description: ${mcpConfig.server.description}`);
  console.log();

  // 2. Available tools summary
  console.log('2. Available Tools Summary:');
  console.log('-'.repeat(70));

  const totalTools = Object.values(mcpTools).reduce((sum, arr) => sum + arr.length, 0);
  console.log(`   Total tools: ${totalTools}`);
  console.log();

  for (const [category, tools] of Object.entries(mcpTools)) {
    console.log(`   ${category.charAt(0).toUpperCase() + category.slice(1)}: ${tools.length} tools`);
    console.log(`     ${tools.slice(0, 4).join(', ')}${tools.length > 4 ? '...' : ''}`);
  }
  console.log();

  // 3. Tool schema examples
  console.log('3. Tool Schema Examples:');
  console.log('-'.repeat(70));

  displayToolSchema('getQuote', {
    description: 'Get current quote for a symbol',
    inputSchema: {
      type: 'object',
      properties: {
        symbol: { type: 'string', description: 'Stock/crypto symbol' },
        extended: { type: 'boolean', default: false, description: 'Include extended data' }
      },
      required: ['symbol']
    }
  });

  displayToolSchema('placeOrder', {
    description: 'Place a trading order',
    inputSchema: {
      type: 'object',
      properties: {
        symbol: { type: 'string', description: 'Trading symbol' },
        side: { type: 'string', enum: ['buy', 'sell'], description: 'Order side' },
        quantity: { type: 'number', description: 'Order quantity' },
        orderType: { type: 'string', enum: ['market', 'limit', 'stop'], default: 'market' },
        limitPrice: { type: 'number', description: 'Limit price (if limit order)' },
        timeInForce: { type: 'string', enum: ['day', 'gtc', 'ioc'], default: 'day' }
      },
      required: ['symbol', 'side', 'quantity']
    }
  });

  displayToolSchema('runBacktest', {
    description: 'Run strategy backtest',
    inputSchema: {
      type: 'object',
      properties: {
        strategy: { type: 'string', description: 'Strategy name or code' },
        symbols: { type: 'array', items: { type: 'string' }, description: 'Symbols to test' },
        startDate: { type: 'string', format: 'date', description: 'Start date' },
        endDate: { type: 'string', format: 'date', description: 'End date' },
        initialCapital: { type: 'number', default: 100000, description: 'Starting capital' }
      },
      required: ['strategy', 'symbols', 'startDate', 'endDate']
    }
  });
  console.log();

  // 4. Example MCP requests
  console.log('4. Example MCP Requests:');
  console.log('-'.repeat(70));

  // Get quote example
  const quoteRequest = {
    jsonrpc: '2.0',
    id: 1,
    method: 'tools/call',
    params: {
      name: 'getQuote',
      arguments: { symbol: 'AAPL', extended: true }
    }
  };
  console.log('   Get Quote Request:');
  console.log(`   ${JSON.stringify(quoteRequest, null, 2).split('\n').join('\n   ')}`);
  console.log();

  const quoteResponse = await simulateToolCall('getQuote', { symbol: 'AAPL', extended: true });
  console.log('   Response:');
  console.log(`   ${JSON.stringify(quoteResponse, null, 2).split('\n').join('\n   ')}`);
  console.log();

  // Place order example
  const orderRequest = {
    jsonrpc: '2.0',
    id: 2,
    method: 'tools/call',
    params: {
      name: 'placeOrder',
      arguments: {
        symbol: 'AAPL',
        side: 'buy',
        quantity: 100,
        orderType: 'limit',
        limitPrice: 180.00
      }
    }
  };
  console.log('   Place Order Request:');
  console.log(`   ${JSON.stringify(orderRequest, null, 2).split('\n').join('\n   ')}`);
  console.log();

  // 5. RuVector integration
  console.log('5. RuVector Integration Features:');
  console.log('-'.repeat(70));

  const integrationFeatures = [
    'Pattern storage for strategy matching',
    'Embedding vectors for news sentiment',
    'Historical signal caching',
    'Neural network weight storage',
    'Trade decision logging with vector search',
    'Real-time pattern similarity detection'
  ];

  integrationFeatures.forEach((feature, i) => {
    console.log(`   ${i + 1}. ${feature}`);
  });
  console.log();

  // 6. Security features
  console.log('6. Security Features:');
  console.log('-'.repeat(70));
  console.log(`   Authentication:   ${mcpConfig.security.requireAuth ? 'Required' : 'Optional'}`);
  console.log(`   Allowed Origins:  ${mcpConfig.security.allowedOrigins.join(', ')}`);
  console.log(`   Rate Limit:       ${mcpConfig.security.rateLimits.requestsPerMinute}/min`);
  console.log(`   Daily Limit:      ${mcpConfig.security.rateLimits.requestsPerHour}/hour`);
  console.log();

  // 7. Claude Code configuration
  console.log('7. Claude Code Configuration:');
  console.log('-'.repeat(70));
  console.log('   Add to your claude_desktop_config.json:');
  console.log();
  console.log(`   {
     "mcpServers": {
       "neural-trader": {
         "command": "npx",
         "args": ["@neural-trader/mcp", "start"],
         "env": {
           "ALPACA_API_KEY": "your-api-key",
           "ALPACA_SECRET_KEY": "your-secret-key"
         }
       }
     }
   }`);
  console.log();

  // 8. Simulate tool calls
  console.log('8. Tool Call Simulation:');
  console.log('-'.repeat(70));

  // Simulate various tool calls
  const simulations = [
    { tool: 'getPortfolioSummary', args: {} },
    { tool: 'calculateIndicator', args: { symbol: 'AAPL', indicator: 'RSI', period: 14 } },
    { tool: 'calculateVaR', args: { confidenceLevel: 0.99, horizon: 1 } },
    { tool: 'predict', args: { symbol: 'AAPL', horizon: 5 } }
  ];

  for (const sim of simulations) {
    console.log(`\n   Tool: ${sim.tool}`);
    console.log(`   Args: ${JSON.stringify(sim.args)}`);
    const result = await simulateToolCall(sim.tool, sim.args);
    console.log(`   Result: ${JSON.stringify(result).substring(0, 80)}...`);
  }
  console.log();

  // 9. Performance metrics
  console.log('9. MCP Server Performance:');
  console.log('-'.repeat(70));
  console.log('   Average latency:  < 10ms (local)');
  console.log('   Throughput:       1000+ requests/sec');
  console.log('   Memory usage:     ~50MB base');
  console.log('   Concurrent:       100+ connections');
  console.log();

  console.log('='.repeat(70));
  console.log('MCP Server integration demo completed!');
  console.log('='.repeat(70));
}

// Display tool schema
function displayToolSchema(name, schema) {
  console.log(`\n   Tool: ${name}`);
  console.log(`   Description: ${schema.description}`);
  console.log('   Parameters:');
  for (const [param, def] of Object.entries(schema.inputSchema.properties)) {
    const required = schema.inputSchema.required?.includes(param) ? '*' : '';
    console.log(`     - ${param}${required}: ${def.type}${def.enum ? ` (${def.enum.join('|')})` : ''}`);
  }
}

// Simulate tool call
async function simulateToolCall(tool, args) {
  // Simulate network latency
  await new Promise(resolve => setTimeout(resolve, 10));

  // Return simulated results based on tool
  switch (tool) {
    case 'getQuote':
      return {
        success: true,
        data: {
          symbol: args.symbol,
          price: 182.52,
          change: 2.35,
          changePercent: 1.30,
          volume: 45234567,
          bid: 182.50,
          ask: 182.54,
          high: 183.21,
          low: 180.15,
          open: 180.45,
          previousClose: 180.17
        }
      };

    case 'getPortfolioSummary':
      return {
        success: true,
        data: {
          totalValue: 985234.56,
          dayChange: 12345.67,
          dayChangePercent: 1.27,
          positions: 15,
          cash: 45678.90,
          marginUsed: 0,
          buyingPower: 145678.90
        }
      };

    case 'calculateIndicator':
      return {
        success: true,
        data: {
          symbol: args.symbol,
          indicator: args.indicator,
          period: args.period,
          values: [
            { date: '2024-12-30', value: 65.4 },
            { date: '2024-12-31', value: 67.2 }
          ],
          signal: 'neutral'
        }
      };

    case 'calculateVaR':
      return {
        success: true,
        data: {
          confidenceLevel: args.confidenceLevel,
          horizon: args.horizon,
          var: 15234.56,
          varPercent: 1.55,
          cvar: 18765.43,
          method: 'historical'
        }
      };

    case 'predict':
      return {
        success: true,
        data: {
          symbol: args.symbol,
          currentPrice: 182.52,
          predictions: [
            { day: 1, price: 183.15, confidence: 0.72 },
            { day: 2, price: 184.20, confidence: 0.68 },
            { day: 3, price: 183.80, confidence: 0.65 },
            { day: 4, price: 185.10, confidence: 0.61 },
            { day: 5, price: 186.50, confidence: 0.58 }
          ],
          trend: 'bullish',
          modelVersion: '2.1.0'
        }
      };

    default:
      return { success: true, data: { message: `Tool ${tool} executed successfully` } };
  }
}

// Run the example
main().catch(console.error);