Gera Tools

Mock JSON Generator

Generate realistic mock JSON records for users, products and posts.

Free mock JSON generator that builds realistic test data for users, products and blog posts. Choose a template and record count to get formatted JSON for your app or tests — it runs entirely in your browser, nothing is uploaded. It runs free in your browser on Gera Tools, with nothing uploaded.

Last updated Source: Gera Tools

What data shapes can I generate?

Three templates are available — users (with name, email, role, city), products (with SKU, price, stock, rating) and blog posts (with title, author, views, slug). Each record uses realistic randomized values.

This tool generates formatted, realistic mock JSON records for stubbing an API, seeding a UI, or writing tests. It produces ready-to-paste data for users, products and blog posts without any backend — everything runs in your browser.

How it works

Pick one of three templates and the generator builds that many records by drawing random values from curated lists (names, cities, roles, product words) and computed fields:

  • user — id, uuid, firstName, lastName, email, city, role
  • product — id, name, SKU, price, stock, rating
  • post — id, title, author, views, slug

Numeric IDs increment from 1 so they stay unique across a batch, and UUIDs are produced with the browser’s secure crypto.randomUUID() so they are well-formed v4 UUIDs. You choose the record count and whether a single record is wrapped in an array.

Example output

Generating one user record produces JSON like:

{
  "id": 1,
  "uuid": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
  "firstName": "Maya",
  "lastName": "Patel",
  "email": "[email protected]",
  "city": "Lisbon",
  "role": "editor"
}

A product batch of three might look like:

[
  { "id": 1, "name": "Wireless Speaker", "sku": "WS-4421", "price": 49.99, "stock": 34, "rating": 4.2 },
  { "id": 2, "name": "Desk Lamp",        "sku": "DL-0087", "price": 29.95, "stock": 12, "rating": 3.8 },
  { "id": 3, "name": "Notebook Set",     "sku": "NS-7760", "price": 12.00, "stock": 88, "rating": 4.6 }
]

When to use each template

TemplateTypical use case
userAuth flows, user-listing UIs, admin dashboards, seeding user tables in tests
productE-commerce frontends, catalog APIs, inventory seeders, filter/sort demos
postBlog or CMS prototypes, search-result placeholders, feed UI mockups

Practical patterns

Seeding a local database. Copy the array output and pipe it into a seed script. Because IDs are sequential and emails use example.com placeholder domains, the data imports cleanly without unique-constraint conflicts.

Mocking an API endpoint. Paste the JSON into json-server, MSW, or Mirage.js as a fixture file. The consistent field shapes mean your frontend components render without prop-type errors or missing-key warnings.

Writing component tests. Generate five or ten records with varied roles, cities, and ratings, then use them as the data prop in a Storybook story or a render() call. Because the data is random on each generation, running the tool again gives you a fresh batch to catch edge cases you might not have thought to write manually.

Demonstrating pagination. Generate 50 product records and use them to build a working paginated table demo. The sequential IDs and varied field values make it easy to demonstrate sort-by-price, filter-by-rating, or page-size changes without a backend.

Tips for clean mock data usage

  • Keep mock data separate from your production code — import it only in test and Storybook files, not in app logic that runs in production.
  • Use example.com and demo.io email domains (which this tool already uses) rather than real domains, to avoid accidentally sending test data to real email addresses during development.
  • If you need consistent data across test runs (for snapshot testing), generate once, commit the JSON file, and import it rather than regenerating each run.

All records are generated entirely in your browser; nothing is uploaded or stored.