AI Mock Data Generator
Generate mock API responses, service stubs, and fake data for frontend development and testing. Create realistic mocks that match your actual API.
Build Frontend Features Without Waiting for the API
Backend and frontend development should not be sequential. With realistic mock data and MSW handlers, frontend developers can build complete features against the agreed API contract before the backend is ready. Our generator creates the mock infrastructure that enables true parallel development across your team.
Every UI State Needs Mock Data
Your UI has more states than just the happy path — loading, empty, error, paginated, single result, and many results. Our generator creates mock data for all these scenarios, ensuring your UI handles every state gracefully. Developing against a single mock response leaves edge states untested until they break in production.
Frequently asked questions
Short answers for this tool before you move into a full branded assistant.
What is the difference between mock data and test data?
Mock data simulates API responses and service outputs for frontend development and prototyping — it represents what your UI will receive at runtime. Test data populates databases and fixtures for backend testing. Our mock data generator focuses on API response shapes, MSW handlers, and mock servers that let you build frontend features independently of the backend.
What mock formats are available?
We generate JSON response data for direct use, Mock Service Worker (MSW) handlers for intercepting API calls in the browser, Express mock server endpoints for standalone mock APIs, Faker.js factory functions for generating dynamic data, and JSON Server db.json files for instant REST APIs. Each format is production-ready and integrates with your development workflow.
Why generate multiple response variations?
Real APIs return different responses based on conditions — populated data, empty results, validation errors, server errors, and paginated results. Generating multiple variations lets you develop and test your UI against all these scenarios. The three-variation preset gives you success data, an empty state, and an error response for comprehensive UI development.
How does data consistency work?
Consistent mode ensures that referenced IDs match across objects — a user ID in a post matches an actual user in the users list. This is critical for testing relationship-dependent features like user profiles linked to posts. Random mode generates independent data for simpler scenarios. Sequential mode uses predictable numbered IDs for easy debugging.
Can I use Mock Service Worker handlers in production builds?
MSW handlers are designed for development and testing only, not production. They intercept network requests at the service worker level, letting your frontend code make real fetch calls that get intercepted and returned with mock data. This is ideal for developing features before the API is ready and for running integration tests without a live server.
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