JSON Schema to Mock Data Generator

Synthesize realistic test JSON data conforming strictly to your JSON Schema, Zod model, or API contract.

Presets:

Count:

JSON Schema DefinitionDraft-07 / OpenAPI compatible

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "format": "uuid"
    },
    "username": {
      "type": "string"
    },
    "email": {
      "type": "string",
      "format": "email"
    },
    "role": {
      "type": "string",
      "enum": [
        "admin",
        "member",
        "editor",
        "viewer"
      ]
    },
    "isActive": {
      "type": "boolean"
    },
    "age": {
      "type": "integer",
      "minimum": 18,
      "maximum": 65
    },
    "preferences": {
      "type": "object",
      "properties": {
        "theme": {
          "type": "string",
          "enum": [
            "dark",
            "light",
            "system"
          ]
        },
        "notifications": {
          "type": "boolean"
        }
      }
    },
    "tags": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "beta-tester",
          "pro",
          "enterprise",
          "early-adopter"
        ]
      },
      "minItems": 1,
      "maxItems": 3
    }
  },
  "required": [
    "id",
    "username",
    "email",
    "role",
    "isActive"
  ]
}

Synthetic Mock Data Result

[
  {
    "id": "2668e0fd-4e03-4198-8bcb-6990896b5845",
    "username": "Jordan Wilson",
    "email": "morgan.jones@startup.ai",
    "role": "viewer",
    "isActive": false,
    "age": 62,
    "preferences": {
      "theme": "system",
      "notifications": true
    },
    "tags": [
      "early-adopter"
    ]
  },
  {
    "id": "99655a3a-6f1d-4f44-850b-fd33945bd4f5",
    "username": "Jordan Brown",
    "email": "jordan.anderson@mail.org",
    "role": "editor",
    "isActive": false,
    "age": 19,
    "preferences": {
      "theme": "dark",
      "notifications": false
    },
    "tags": [
      "early-adopter"
    ]
  },
  {
    "id": "863f90df-6832-4c32-84e9-5e5c925a2175",
    "username": "Jordan Taylor",
    "email": "jamie.davis@startup.ai",
    "role": "editor",
    "isActive": true,
    "age": 27,
    "preferences": {
      "theme": "light",
      "notifications": true
    },
    "tags": [
      "pro"
    ]
  }
]

Testing LLM Structured Outputs & APIs with Synthetic Data

As modern backend and AI applications shift toward JSON Schema-constrained structured outputs (such as OpenAI response_format: json_schema or Anthropic Tool Calling), generating realistic mock datasets is essential for automated testing, prompt evaluation, and UI frontend prototyping without incurring API costs.

Why Use In-Browser Schema Mocking?

Deterministic Rule Enforcement: Automatically validates and conforms to type specifications (strings, numbers, integers, booleans, enums, min/max limits, array lengths, and nested child structures).
Complete Privacy: Entirely executed in client-side JavaScript. No schema definitions, internal data contracts, or PII templates ever touch a server.
Rapid API Prototyping: Enables frontend engineers to unblock UI development before backend endpoints or LLM agent pipelines are deployed.

Compatible Schema Standards

This mock synthesizer works with standard JSON Schema Draft-07, Draft-04, OpenAPI 3.0 / 3.1 schema blocks, and schemas generated by tools like Zod, Pydantic, and TypeBox.