MCP Server Transaction Management for ChatGPT Apps

Building reliable ChatGPT applications with Model Context Protocol (MCP) servers requires robust transaction management to ensure data consistency, prevent race conditions, and maintain system integrity. Whether you're implementing booking systems, payment processing, or multi-step workflows, understanding ACID properties and transaction patterns is critical for production-ready MCP servers.

Transaction management becomes especially challenging in distributed MCP architectures where multiple services must coordinate state changes. A booking confirmation might involve checking inventory, charging payment, sending notifications, and updating multiple databases—all requiring atomic execution. Without proper transaction management, partial failures can leave your system in inconsistent states.

This comprehensive guide covers database transactions, distributed transaction patterns (including saga orchestration), concurrency control strategies, and performance optimization techniques. You'll learn production-ready implementations using TypeScript, PostgreSQL, and Firestore, with real-world examples of handling failures, deadlocks, and distributed coordination.

ACID properties form the foundation: Atomicity ensures all-or-nothing execution, Consistency maintains database constraints, Isolation prevents interference between concurrent transactions, and Durability guarantees committed changes survive failures. Master these principles to build ChatGPT apps that scale reliably.

Database Transactions: Foundation of Data Consistency

Database transactions provide atomicity and isolation for operations that must execute as indivisible units. PostgreSQL, MySQL, and other RDBMS systems offer robust transaction support with BEGIN, COMMIT, and ROLLBACK commands. Understanding isolation levels and transaction lifecycle management is essential for MCP server reliability.

PostgreSQL Transaction Wrapper

This production-ready transaction wrapper provides automatic retry logic, connection pooling, and comprehensive error handling:

import { Pool, PoolClient } from 'pg';

interface TransactionOptions {
  isolationLevel?: 'READ UNCOMMITTED' | 'READ COMMITTED' | 'REPEATABLE READ' | 'SERIALIZABLE';
  maxRetries?: number;
  retryDelay?: number;
  timeout?: number;
}

interface TransactionMetrics {
  startTime: number;
  endTime?: number;
  duration?: number;
  retryCount: number;
  status: 'pending' | 'committed' | 'rolled_back' | 'failed';
  error?: Error;
}

class DatabaseTransactionManager {
  private pool: Pool;
  private metrics: Map<string, TransactionMetrics>;

  constructor(connectionString: string) {
    this.pool = new Pool({
      connectionString,
      max: 20, // Maximum pool connections
      idleTimeoutMillis: 30000,
      connectionTimeoutMillis: 5000,
    });
    this.metrics = new Map();
  }

  /**
   * Execute a transaction with automatic retry and rollback on failure
   */
  async executeTransaction<T>(
    transactionId: string,
    callback: (client: PoolClient) => Promise<T>,
    options: TransactionOptions = {}
  ): Promise<T> {
    const {
      isolationLevel = 'READ COMMITTED',
      maxRetries = 3,
      retryDelay = 100,
      timeout = 30000,
    } = options;

    const metric: TransactionMetrics = {
      startTime: Date.now(),
      retryCount: 0,
      status: 'pending',
    };
    this.metrics.set(transactionId, metric);

    let lastError: Error | undefined;

    for (let attempt = 0; attempt <= maxRetries; attempt++) {
      const client = await this.pool.connect();

      try {
        // Set transaction isolation level
        await client.query(`SET TRANSACTION ISOLATION LEVEL ${isolationLevel}`);

        // Begin transaction with timeout
        await client.query('BEGIN');
        const timeoutPromise = new Promise<never>((_, reject) =>
          setTimeout(() => reject(new Error('Transaction timeout')), timeout)
        );

        // Execute callback with timeout protection
        const result = await Promise.race([
          callback(client),
          timeoutPromise,
        ]);

        // Commit transaction
        await client.query('COMMIT');

        metric.status = 'committed';
        metric.endTime = Date.now();
        metric.duration = metric.endTime - metric.startTime;

        return result;

      } catch (error: any) {
        // Rollback on any error
        await client.query('ROLLBACK').catch(() => {});

        lastError = error;
        metric.retryCount = attempt;
        metric.error = error;

        // Check if error is retryable (deadlock, serialization failure)
        const isRetryable = this.isRetryableError(error);

        if (!isRetryable || attempt === maxRetries) {
          metric.status = 'failed';
          metric.endTime = Date.now();
          metric.duration = metric.endTime - metric.startTime;
          throw error;
        }

        // Exponential backoff before retry
        await new Promise(resolve =>
          setTimeout(resolve, retryDelay * Math.pow(2, attempt))
        );

      } finally {
        client.release();
      }
    }

    throw lastError || new Error('Transaction failed after retries');
  }

  /**
   * Determine if database error is retryable
   */
  private isRetryableError(error: any): boolean {
    const retryableCodes = [
      '40001', // serialization_failure
      '40P01', // deadlock_detected
      '08006', // connection_failure
      '08003', // connection_does_not_exist
    ];

    return retryableCodes.includes(error.code);
  }

  /**
   * Get transaction metrics for monitoring
   */
  getMetrics(transactionId: string): TransactionMetrics | undefined {
    return this.metrics.get(transactionId);
  }

  /**
   * Close pool connections
   */
  async close(): Promise<void> {
    await this.pool.end();
  }
}

// Usage example: Multi-step booking transaction
async function createBookingTransaction(
  manager: DatabaseTransactionManager,
  userId: string,
  classId: string,
  paymentAmount: number
) {
  const transactionId = `booking-${userId}-${Date.now()}`;

  return manager.executeTransaction(
    transactionId,
    async (client) => {
      // Check class availability
      const classCheck = await client.query(
        'SELECT available_spots FROM classes WHERE id = $1 FOR UPDATE',
        [classId]
      );

      if (classCheck.rows[0].available_spots <= 0) {
        throw new Error('No available spots');
      }

      // Decrement available spots
      await client.query(
        'UPDATE classes SET available_spots = available_spots - 1 WHERE id = $1',
        [classId]
      );

      // Create booking record
      const booking = await client.query(
        'INSERT INTO bookings (user_id, class_id, status) VALUES ($1, $2, $3) RETURNING id',
        [userId, classId, 'confirmed']
      );

      // Process payment
      await client.query(
        'INSERT INTO payments (booking_id, amount, status) VALUES ($1, $2, $3)',
        [booking.rows[0].id, paymentAmount, 'completed']
      );

      // Update user credits
      await client.query(
        'UPDATE users SET credits = credits - 1 WHERE id = $1',
        [userId]
      );

      return { bookingId: booking.rows[0].id };
    },
    { isolationLevel: 'SERIALIZABLE', maxRetries: 5 }
  );
}

Firestore Batch Transactions

Firestore provides atomic batch operations and transactions for NoSQL data consistency:

import { Firestore, WriteBatch, Transaction } from '@google-cloud/firestore';

class FirestoreTransactionManager {
  private db: Firestore;
  private maxBatchSize = 500; // Firestore limit

  constructor(projectId: string) {
    this.db = new Firestore({ projectId });
  }

  /**
   * Execute Firestore transaction with optimistic concurrency control
   */
  async executeTransaction<T>(
    transactionId: string,
    callback: (transaction: Transaction) => Promise<T>
  ): Promise<T> {
    const startTime = Date.now();

    try {
      const result = await this.db.runTransaction(async (transaction) => {
        return await callback(transaction);
      });

      console.log(`Transaction ${transactionId} completed in ${Date.now() - startTime}ms`);
      return result;

    } catch (error: any) {
      console.error(`Transaction ${transactionId} failed:`, error.message);
      throw error;
    }
  }

  /**
   * Execute batch write (no read operations)
   */
  async executeBatch(
    operations: Array<{ type: 'set' | 'update' | 'delete'; ref: any; data?: any }>
  ): Promise<void> {
    const batches: WriteBatch[] = [];
    let currentBatch = this.db.batch();
    let operationCount = 0;

    for (const op of operations) {
      if (operationCount >= this.maxBatchSize) {
        batches.push(currentBatch);
        currentBatch = this.db.batch();
        operationCount = 0;
      }

      switch (op.type) {
        case 'set':
          currentBatch.set(op.ref, op.data);
          break;
        case 'update':
          currentBatch.update(op.ref, op.data);
          break;
        case 'delete':
          currentBatch.delete(op.ref);
          break;
      }

      operationCount++;
    }

    if (operationCount > 0) {
      batches.push(currentBatch);
    }

    // Commit all batches sequentially
    for (const batch of batches) {
      await batch.commit();
    }
  }
}

// Usage: Multi-document booking transaction
async function createFirestoreBooking(
  manager: FirestoreTransactionManager,
  userId: string,
  classId: string
) {
  return manager.executeTransaction(
    `booking-${userId}-${classId}`,
    async (transaction) => {
      const classRef = manager['db'].collection('classes').doc(classId);
      const userRef = manager['db'].collection('users').doc(userId);
      const bookingRef = manager['db'].collection('bookings').doc();

      // Read current state
      const [classDoc, userDoc] = await Promise.all([
        transaction.get(classRef),
        transaction.get(userRef),
      ]);

      const availableSpots = classDoc.data()?.availableSpots || 0;
      const userCredits = userDoc.data()?.credits || 0;

      // Validate constraints
      if (availableSpots <= 0) {
        throw new Error('No available spots');
      }
      if (userCredits <= 0) {
        throw new Error('Insufficient credits');
      }

      // Atomic updates
      transaction.update(classRef, {
        availableSpots: availableSpots - 1,
        updatedAt: new Date(),
      });

      transaction.update(userRef, {
        credits: userCredits - 1,
        updatedAt: new Date(),
      });

      transaction.set(bookingRef, {
        userId,
        classId,
        status: 'confirmed',
        createdAt: new Date(),
      });

      return { bookingId: bookingRef.id };
    }
  );
}

For comprehensive database optimization strategies, see our guide on database optimization for ChatGPT apps.

Distributed Transactions: Saga Pattern Implementation

Distributed transactions coordinate multiple services or databases that cannot participate in a single ACID transaction. The saga pattern breaks long-running transactions into smaller, compensatable steps with rollback logic for partial failures. This approach is essential for microservices architectures and multi-tenant MCP servers.

Saga Orchestrator

This orchestrator manages complex multi-step workflows with automatic compensation on failure:

interface SagaStep<T = any, C = any> {
  name: string;
  execute: (context: T) => Promise<C>;
  compensate: (context: T, result?: C) => Promise<void>;
  timeout?: number;
}

interface SagaContext {
  sagaId: string;
  status: 'running' | 'completed' | 'compensating' | 'failed';
  completedSteps: string[];
  compensationResults: Map<string, any>;
  errors: Error[];
  startTime: number;
  endTime?: number;
}

class SagaOrchestrator<T = any> {
  private steps: SagaStep<T>[] = [];
  private context: SagaContext;
  private compensationTimeout = 5000;

  constructor(sagaId: string) {
    this.context = {
      sagaId,
      status: 'running',
      completedSteps: [],
      compensationResults: new Map(),
      errors: [],
      startTime: Date.now(),
    };
  }

  /**
   * Add step to saga workflow
   */
  addStep(step: SagaStep<T>): this {
    this.steps.push(step);
    return this;
  }

  /**
   * Execute saga with automatic compensation on failure
   */
  async execute(initialContext: T): Promise<{ success: boolean; context: SagaContext }> {
    const stepResults = new Map<string, any>();

    try {
      // Execute steps sequentially
      for (const step of this.steps) {
        console.log(`Executing saga step: ${step.name}`);

        const timeout = step.timeout || 10000;
        const timeoutPromise = new Promise<never>((_, reject) =>
          setTimeout(() => reject(new Error(`Step ${step.name} timeout`)), timeout)
        );

        try {
          const result = await Promise.race([
            step.execute(initialContext),
            timeoutPromise,
          ]);

          stepResults.set(step.name, result);
          this.context.completedSteps.push(step.name);

        } catch (stepError: any) {
          console.error(`Step ${step.name} failed:`, stepError.message);
          this.context.errors.push(stepError);

          // Trigger compensation for all completed steps
          await this.compensate(initialContext, stepResults);

          this.context.status = 'failed';
          this.context.endTime = Date.now();
          return { success: false, context: this.context };
        }
      }

      // All steps completed successfully
      this.context.status = 'completed';
      this.context.endTime = Date.now();
      return { success: true, context: this.context };

    } catch (error: any) {
      console.error('Saga execution failed:', error.message);
      this.context.errors.push(error);
      this.context.status = 'failed';
      this.context.endTime = Date.now();
      return { success: false, context: this.context };
    }
  }

  /**
   * Compensate completed steps in reverse order
   */
  private async compensate(
    initialContext: T,
    stepResults: Map<string, any>
  ): Promise<void> {
    console.log('Starting compensation for completed steps');
    this.context.status = 'compensating';

    // Reverse order compensation
    const completedSteps = [...this.context.completedSteps].reverse();

    for (const stepName of completedSteps) {
      const step = this.steps.find(s => s.name === stepName);
      if (!step) continue;

      try {
        console.log(`Compensating step: ${stepName}`);

        const timeoutPromise = new Promise<never>((_, reject) =>
          setTimeout(
            () => reject(new Error(`Compensation timeout for ${stepName}`)),
            this.compensationTimeout
          )
        );

        const result = stepResults.get(stepName);
        await Promise.race([
          step.compensate(initialContext, result),
          timeoutPromise,
        ]);

        this.context.compensationResults.set(stepName, 'success');

      } catch (compError: any) {
        console.error(`Compensation failed for ${stepName}:`, compError.message);
        this.context.compensationResults.set(stepName, 'failed');
        this.context.errors.push(compError);
      }
    }
  }

  /**
   * Get saga execution metrics
   */
  getMetrics(): SagaContext {
    return { ...this.context };
  }
}

// Usage: E-commerce order saga
interface OrderContext {
  orderId: string;
  userId: string;
  items: Array<{ productId: string; quantity: number }>;
  totalAmount: number;
  paymentMethod: string;
}

async function executeOrderSaga(orderContext: OrderContext) {
  const saga = new SagaOrchestrator<OrderContext>(`order-${orderContext.orderId}`);

  // Step 1: Reserve inventory
  saga.addStep({
    name: 'reserve_inventory',
    execute: async (ctx) => {
      const reservations = [];
      for (const item of ctx.items) {
        const reserved = await inventoryService.reserve(item.productId, item.quantity);
        reservations.push({ productId: item.productId, reservationId: reserved.id });
      }
      return reservations;
    },
    compensate: async (ctx, reservations) => {
      if (!reservations) return;
      for (const res of reservations) {
        await inventoryService.releaseReservation(res.reservationId);
      }
    },
  });

  // Step 2: Process payment
  saga.addStep({
    name: 'process_payment',
    execute: async (ctx) => {
      const payment = await paymentService.charge({
        userId: ctx.userId,
        amount: ctx.totalAmount,
        method: ctx.paymentMethod,
      });
      return { transactionId: payment.transactionId };
    },
    compensate: async (ctx, payment) => {
      if (!payment) return;
      await paymentService.refund(payment.transactionId);
    },
  });

  // Step 3: Create order record
  saga.addStep({
    name: 'create_order',
    execute: async (ctx) => {
      const order = await orderService.create({
        orderId: ctx.orderId,
        userId: ctx.userId,
        items: ctx.items,
        status: 'confirmed',
      });
      return { orderId: order.id };
    },
    compensate: async (ctx, order) => {
      if (!order) return;
      await orderService.cancel(order.orderId);
    },
  });

  // Step 4: Send confirmation email
  saga.addStep({
    name: 'send_confirmation',
    execute: async (ctx) => {
      await emailService.sendOrderConfirmation(ctx.userId, ctx.orderId);
      return { emailSent: true };
    },
    compensate: async (ctx) => {
      // Email cannot be unsent, log for manual follow-up
      console.log(`Manual follow-up required: cancellation email for ${ctx.orderId}`);
    },
  });

  return saga.execute(orderContext);
}

For distributed system design patterns, explore our distributed systems guide for ChatGPT apps.

Transaction Boundaries: Scope and Savepoints

Defining proper transaction boundaries prevents unnecessary locking and improves concurrency. Nested transactions and savepoints allow partial rollback within larger transactions, enabling sophisticated error recovery strategies.

Savepoint Manager

class SavepointManager {
  private savepoints: Map<string, string[]>;

  constructor() {
    this.savepoints = new Map();
  }

  /**
   * Create savepoint within transaction
   */
  async createSavepoint(
    client: PoolClient,
    transactionId: string,
    savepointName: string
  ): Promise<void> {
    await client.query(`SAVEPOINT ${savepointName}`);

    const existing = this.savepoints.get(transactionId) || [];
    existing.push(savepointName);
    this.savepoints.set(transactionId, existing);
  }

  /**
   * Rollback to savepoint (partial rollback)
   */
  async rollbackToSavepoint(
    client: PoolClient,
    transactionId: string,
    savepointName: string
  ): Promise<void> {
    await client.query(`ROLLBACK TO SAVEPOINT ${savepointName}`);

    // Remove subsequent savepoints
    const existing = this.savepoints.get(transactionId) || [];
    const index = existing.indexOf(savepointName);
    if (index !== -1) {
      this.savepoints.set(transactionId, existing.slice(0, index + 1));
    }
  }

  /**
   * Release savepoint (cannot rollback past this point)
   */
  async releaseSavepoint(
    client: PoolClient,
    transactionId: string,
    savepointName: string
  ): Promise<void> {
    await client.query(`RELEASE SAVEPOINT ${savepointName}`);

    const existing = this.savepoints.get(transactionId) || [];
    const index = existing.indexOf(savepointName);
    if (index !== -1) {
      existing.splice(index, 1);
      this.savepoints.set(transactionId, existing);
    }
  }

  /**
   * Clean up transaction savepoints
   */
  cleanup(transactionId: string): void {
    this.savepoints.delete(transactionId);
  }
}

// Usage: Complex booking with partial rollback
async function bookingWithSavepoints(
  manager: DatabaseTransactionManager,
  savepointMgr: SavepointManager,
  userId: string,
  classId: string
) {
  return manager.executeTransaction(
    `booking-${userId}-${classId}`,
    async (client) => {
      const transactionId = `booking-${userId}-${classId}`;

      // Main booking logic
      await savepointMgr.createSavepoint(client, transactionId, 'after_inventory_check');

      try {
        // Attempt premium processing
        await client.query('UPDATE users SET premium_attempts = premium_attempts + 1 WHERE id = $1', [userId]);

        await savepointMgr.createSavepoint(client, transactionId, 'after_premium_processing');

        // If premium fails, rollback only premium changes
      } catch (error) {
        await savepointMgr.rollbackToSavepoint(client, transactionId, 'after_inventory_check');
        console.log('Premium processing failed, continuing with standard booking');
      }

      // Continue with standard booking
      const booking = await client.query(
        'INSERT INTO bookings (user_id, class_id) VALUES ($1, $2) RETURNING id',
        [userId, classId]
      );

      savepointMgr.cleanup(transactionId);
      return { bookingId: booking.rows[0].id };
    }
  );
}

Concurrency Control: Locking Strategies

Concurrent transactions can cause race conditions, lost updates, and inconsistent reads. Optimistic locking uses version numbers to detect conflicts, while pessimistic locking prevents concurrent access entirely. Choose the right strategy based on conflict probability and performance requirements.

Optimistic Locking Implementation

interface VersionedEntity {
  id: string;
  version: number;
  data: any;
  updatedAt: Date;
}

class OptimisticLockManager {
  /**
   * Update entity with optimistic locking (version-based)
   */
  async updateWithOptimisticLock(
    client: PoolClient,
    tableName: string,
    entityId: string,
    currentVersion: number,
    updates: Record<string, any>,
    maxRetries: number = 5
  ): Promise<VersionedEntity> {
    for (let attempt = 0; attempt < maxRetries; attempt++) {
      try {
        // Attempt update with version check
        const result = await client.query(
          `UPDATE ${tableName}
           SET ${Object.keys(updates).map((k, i) => `${k} = $${i + 3}`).join(', ')},
               version = version + 1,
               updated_at = NOW()
           WHERE id = $1 AND version = $2
           RETURNING *`,
          [entityId, currentVersion, ...Object.values(updates)]
        );

        if (result.rowCount === 0) {
          // Version mismatch - entity was modified by another transaction
          if (attempt < maxRetries - 1) {
            // Fetch current version and retry
            const current = await client.query(
              `SELECT * FROM ${tableName} WHERE id = $1`,
              [entityId]
            );

            if (current.rowCount === 0) {
              throw new Error(`Entity ${entityId} not found`);
            }

            currentVersion = current.rows[0].version;

            // Exponential backoff
            await new Promise(resolve =>
              setTimeout(resolve, Math.pow(2, attempt) * 50)
            );
            continue;
          }

          throw new Error(`Optimistic lock failure after ${maxRetries} retries`);
        }

        return result.rows[0];

      } catch (error: any) {
        if (attempt === maxRetries - 1) {
          throw error;
        }
      }
    }

    throw new Error('Update failed after maximum retries');
  }

  /**
   * Batch update with optimistic locking
   */
  async batchUpdateWithOptimisticLock(
    client: PoolClient,
    tableName: string,
    updates: Array<{ id: string; version: number; data: Record<string, any> }>
  ): Promise<{ successful: string[]; failed: Array<{ id: string; reason: string }> }> {
    const successful: string[] = [];
    const failed: Array<{ id: string; reason: string }> = [];

    for (const update of updates) {
      try {
        await this.updateWithOptimisticLock(
          client,
          tableName,
          update.id,
          update.version,
          update.data
        );
        successful.push(update.id);

      } catch (error: any) {
        failed.push({ id: update.id, reason: error.message });
      }
    }

    return { successful, failed };
  }
}

Deadlock Retry Handler

class DeadlockRetryHandler {
  /**
   * Execute operation with automatic deadlock retry
   */
  async executeWithDeadlockRetry<T>(
    operation: () => Promise<T>,
    maxRetries: number = 3,
    baseDelay: number = 100
  ): Promise<T> {
    let lastError: Error | undefined;

    for (let attempt = 0; attempt <= maxRetries; attempt++) {
      try {
        return await operation();

      } catch (error: any) {
        lastError = error;

        // Check if deadlock error
        if (error.code !== '40P01') {
          throw error;
        }

        if (attempt === maxRetries) {
          throw new Error(`Deadlock persists after ${maxRetries} retries: ${error.message}`);
        }

        // Randomized exponential backoff to avoid thundering herd
        const jitter = Math.random() * 0.3 + 0.85; // 0.85-1.15
        const delay = baseDelay * Math.pow(2, attempt) * jitter;

        console.log(`Deadlock detected, retrying in ${Math.round(delay)}ms (attempt ${attempt + 1}/${maxRetries})`);
        await new Promise(resolve => setTimeout(resolve, delay));
      }
    }

    throw lastError || new Error('Operation failed');
  }
}

// Usage: Concurrent updates with deadlock handling
async function updateUserBalances(
  manager: DatabaseTransactionManager,
  fromUserId: string,
  toUserId: string,
  amount: number
) {
  const deadlockHandler = new DeadlockRetryHandler();

  return deadlockHandler.executeWithDeadlockRetry(async () => {
    return manager.executeTransaction(
      `transfer-${fromUserId}-${toUserId}`,
      async (client) => {
        // Lock rows in consistent order to prevent deadlock (alphabetically by ID)
        const [firstId, secondId] = [fromUserId, toUserId].sort();

        // Lock first user
        await client.query(
          'SELECT * FROM users WHERE id = $1 FOR UPDATE',
          [firstId]
        );

        // Lock second user
        await client.query(
          'SELECT * FROM users WHERE id = $1 FOR UPDATE',
          [secondId]
        );

        // Perform transfer
        await client.query(
          'UPDATE users SET balance = balance - $1 WHERE id = $2',
          [amount, fromUserId]
        );

        await client.query(
          'UPDATE users SET balance = balance + $1 WHERE id = $2',
          [amount, toUserId]
        );

        return { success: true };
      },
      { isolationLevel: 'SERIALIZABLE' }
    );
  });
}

Learn more about saga patterns in our saga pattern implementation guide for ChatGPT apps.

Performance Optimization: Transaction Efficiency

Transaction performance directly impacts user experience and system scalability. Batching operations, connection pooling, and strategic indexing reduce overhead while maintaining consistency guarantees.

Transaction Metrics Tracker

interface TransactionMetricsSnapshot {
  transactionId: string;
  duration: number;
  retryCount: number;
  queryCount: number;
  rowsAffected: number;
  isolationLevel: string;
  status: string;
}

class TransactionMetricsTracker {
  private metrics: Map<string, TransactionMetricsSnapshot[]>;

  constructor() {
    this.metrics = new Map();
  }

  /**
   * Record transaction metrics
   */
  recordTransaction(snapshot: TransactionMetricsSnapshot): void {
    const existing = this.metrics.get(snapshot.transactionId) || [];
    existing.push(snapshot);
    this.metrics.set(snapshot.transactionId, existing);
  }

  /**
   * Get performance statistics
   */
  getStatistics(): {
    averageDuration: number;
    p95Duration: number;
    totalRetries: number;
    failureRate: number;
  } {
    const allSnapshots = Array.from(this.metrics.values()).flat();

    if (allSnapshots.length === 0) {
      return { averageDuration: 0, p95Duration: 0, totalRetries: 0, failureRate: 0 };
    }

    const durations = allSnapshots.map(s => s.duration).sort((a, b) => a - b);
    const averageDuration = durations.reduce((a, b) => a + b, 0) / durations.length;
    const p95Index = Math.floor(durations.length * 0.95);
    const p95Duration = durations[p95Index] || durations[durations.length - 1];

    const totalRetries = allSnapshots.reduce((sum, s) => sum + s.retryCount, 0);
    const failures = allSnapshots.filter(s => s.status === 'failed').length;
    const failureRate = failures / allSnapshots.length;

    return { averageDuration, p95Duration, totalRetries, failureRate };
  }
}

For complete MCP server architecture guidance, explore our pillar guide on building ChatGPT applications.

Conclusion: Building Reliable Transactional Systems

Mastering transaction management is essential for production-ready MCP servers powering ChatGPT applications. ACID database transactions provide strong consistency guarantees for single-database operations, while saga patterns enable distributed coordination across microservices. Optimistic locking minimizes contention for low-conflict scenarios, while pessimistic locking prevents concurrent access when data integrity is critical.

The key is choosing the right pattern for your use case: use database transactions for atomic operations within a single database, implement saga orchestration for multi-service workflows, apply optimistic locking for high-concurrency reads with occasional writes, and leverage savepoints for complex transactions requiring partial rollback capability.

Performance optimization through connection pooling, transaction batching, and strategic indexing ensures your transactional systems scale efficiently. Monitor transaction metrics to identify bottlenecks, tune isolation levels based on consistency requirements, and implement exponential backoff retry strategies for transient failures.

Ready to build ChatGPT apps with enterprise-grade transaction management? Try MakeAIHQ's no-code platform and deploy production-ready MCP servers with built-in transactional patterns, automatic retry logic, and distributed coordination—no database expertise required. From zero to ChatGPT App Store in 48 hours.

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Related Resources:

• Complete Guide to Building ChatGPT Applications
• Database Optimization for ChatGPT Apps
• Distributed Systems Design for ChatGPT
• Saga Pattern Implementation Guide

External References:

• PostgreSQL Transaction Isolation
• Saga Pattern Documentation
• ACID Properties Explained