JSON Schema to Mock JSON
Generate deterministic mock JSON data from JSON Schema Draft 2020-12 and Draft-07. Supports valid fixtures, boundary checks, and edge cases.
About this json schema to mock json
This developer tool traverses a JSON Schema document and deterministically synthesizes sample JSON payloads adhering to your exact data types, constraints, and formats. It supports generation modes for standard valid fixtures, minimum and maximum boundary testing, and intentional schema violations for error-handling verification. Every mock payload is compiled and validated against the source schema in your browser.
Deterministic generation and reproducible test fixtures
Traditional mock data generators produce random values that change between runs, making them unsuitable for snapshot testing, reproducible bug reports, and version-controlled API contract tests. This generator uses a seeded pseudo-random number function (seeded PRNG) to produce the same mock data from the same schema and seed on every run, across browsers and operating systems. This determinism enables fixtures to be committed to version control alongside tests and regenerated on demand when the schema changes. The seed value can be changed to produce a different but equally deterministic fixture for boundary and edge-case testing scenarios.
Mock generation for testing patterns
Well-structured API test suites typically need three categories of mock fixtures: valid payloads that satisfy all schema constraints for happy-path testing, boundary payloads that contain minimum and maximum allowed values for numeric and string properties for limit testing, and invalid payloads with deliberate schema violations for error-response testing. This tool generates all three categories from a single schema source. For API contract testing frameworks such as Pact or Dredd, the valid fixture can serve as the provider-state example, while the invalid fixture verifies that the server returns an appropriate 400 Bad Request or 422 Unprocessable Entity response with a structured error body. It supports generation modes for standard valid fixtures, minimum and maximum boundary testing, and intentional schema violations for error-handling verification. Every mock payload is compiled and validated against the source schema in your browser.
Worked constrained-response example
A required integer with minimum 1 and maximum 9,999 receives an in-range value. An email format receives a syntactically valid example, and an enum selects only one declared member.
Minimum and maximum modes target declared boundaries. Intentional-invalid mode removes a required property or changes a root type, then confirms that validation fails.
Deterministic and reviewable
The same schema, mode, and seed produce the same output. The generator gives precedence to const, examples, default, and enum values before synthesizing a type-based value.
Limits that are reported, not hidden
- Local references are resolved; external references are not fetched.
- Recursive references and very large arrays are capped to keep the browser responsive.
- Arbitrary regular-expression patterns are not guessed. Supply an example when a pattern must be satisfied.
- A valid mock proves schema conformance only; it does not prove that the value is realistic for a particular business domain.
JSON Schema 2020-12 · Content owner: CZOA Tools · Review methodology
How to use it
- Paste a Draft 2020-12 or Draft-07 JSON Schema.
- Choose standard, minimum, maximum, or intentional-invalid mode and a repeatable seed.
- Generate the mock and read the actual validation result.
- Use business-specific examples for formats or patterns that structural rules cannot synthesize reliably.
Frequently asked questions
How does JSON Schema to Mock JSON generate a result?+
It reads a JSON Schema, a generation mode, and numeric seed. Standard, minimum, maximum, and intentional-invalid modes produce a local output and show schema validity, expected validity, and actual validation as separate page facts.
Can you show an input and its result?+
For a closed object requiring integer n from 3 through 5, enum tag a or b, and boolean flag, the generated output contained exactly those three conforming properties. The page reported a valid schema, expected valid result, and actual validation valid.
What does a valid mock demonstrate?+
It demonstrates conformance of that generated value to the submitted schema under the selected mode and seed. It does not establish realistic domain data, server behavior, external reference resolution, or that every JSON Schema keyword has a generator strategy.
How should intentional-invalid mode be read?+
That mode is designed to request an invalid sample and compare expected versus actual validation. Its result is useful only when the page shows that the requested invalid state was actually reached; do not treat malformed output alone as a verified negative test.