LocalMock — Free Mock Data Generator
LocalMock is a free mock data generator and test data generator for developers, QA engineers, product teams, and AI assistants. It creates realistic fake data, sample data, dummy data, seed data, and API mock payloads in the browser.
Use LocalMock when you need CSV test data, JSON mock data, SQL insert data, JSONL files, MSW handlers, or TypeScript arrays. These exports fit tests, demos, prototypes, docs, and local development.
The app supports manual fields, reusable templates, Prisma schemas, TypeScript types, JSON schemas, multi-table relations, and chaos testing fields. These options help teams create useful messy edge-case data without writing a new fixture script each time.
Unlike server-first fake data generators, LocalMock keeps schemas and generated data on your device. This helps with private database models, customer-like sample datasets, API mocks, seed scripts, and repeatable QA workflows.
For AI-assisted work, LocalMock is better than asking a chat assistant to print thousands of rows. An assistant can help design the schema. LocalMock can then generate the large dataset locally and export it in the format you need.
- Generate private mock data and test data in the browser.
- Export CSV, JSON, JSONL, SQL, MSW, and TypeScript data.
- Create relational mock data with foreign key integrity.
- Build fake users, products, orders, invoices, logs, events, addresses, support tickets, and more.
- Use chaos testing options to produce nulls, formatting issues, broken encoding, and other realistic data problems.
Private mock data for developer workflows
LocalMock is designed for practical software testing work. A developer can paste an existing schema, describe fields manually, or start from templates. Common templates include users, orders, products, invoices, server metrics, API logs, students, subscriptions, real estate listings, chat messages, comments, and support tickets.
The goal is to create realistic records quickly. You should not need a custom script for every mock dataset.
Because generation happens client-side, LocalMock is useful when schemas contain private business names, internal fields, customer-like attributes, or app-specific table structures. The tool can produce a small preview for review. It can then export larger datasets for local files, fixture folders, seed commands, API mocks, or integration tests.
Schema-aware fake data generation
LocalMock supports schema-aware generation for teams that need more than random names and emails. Prisma, TypeScript, and JSON inputs can become structured test data fields. Manual editing gives direct control over field names, data types, uniqueness, and export shape.
Multi-table generation helps preserve relationships between records. Orders can point to users, line items can point to products, and seed data can keep foreign keys consistent.
The chaos engine is useful when applications must handle imperfect real-world data. It can introduce nulls, whitespace, broken encoding, casing problems, and other edge cases. This helps test validation, import pipelines, dashboards, and API clients before production users find the issue.
Exports for testing, demos, and API mocks
LocalMock exports developer-friendly formats instead of locking data into one workflow. CSV works for spreadsheets and import tests. JSON and JSONL work for APIs and event streams. SQL inserts work for database seeding. MSW handlers support frontend API mocking. TypeScript arrays work well inside unit tests, Storybook stories, prototypes, and documentation examples.
For AI assistants and coding agents, LocalMock provides a focused execution step. The assistant can help plan the schema and recommend fields. LocalMock handles bulk generation locally. That avoids wasting context on thousands of printed rows and gives the user a reusable interface for changing row counts, export formats, and data quality settings.
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