Infer JSON Schema from a sample

API and application teams use JSON Schema Generator to draft types, validation rules or documentation from sample data.

Infer JSON Schema from a sample, then refine the generated structure for your project. Use it for free in your browser, with no account required.

How to use

Place a representative JSON sample in the input area, or import a file from your device.
Click the Generate button so the tool infers the structure of your data.
Look through the JSON schema that appears in the result area.
Check the types, properties and required fields, then copy the schema.
If needed, edit the schema manually to add constraints the tool did not detect.

Example

Suppose you need to validate API responses. Paste a sample JSON response, generate the schema, and use it as a starting point for your tests. You will immediately see the structure of objects and arrays.

Limits and formats

The schema is inferred from a single example: it cannot guess variants missing from your sample.
Format rules (dates, emails) or numeric constraints are not automatically added.
A poor sample leads to an imprecise schema; always review the result before using it.
This tool does not validate your data against the schema; it only produces the schema.

Where processing happens

Processing is entirely local: your browser runs the analysis and nothing is sent out. You can therefore paste snippets of real data without fearing a leak, as long as you stay in control of your screen.

Frequently asked questions

What happens if my JSON sample is invalid?

The tool needs valid JSON to infer a schema. If your sample contains a syntax error, generation will fail and no result will appear. Fix your JSON first, then run the operation again.

Can I generate a schema for an array at the root?

Yes, a JSON array at the root is accepted. The generated schema will then describe an array and, if items are present, the structure of those items. With no items, the object type remains undefined.

Is the produced schema directly usable to validate data?

It gives a useful base, but it only reflects the sample you provided. For reliable validation, complete it with business constraints and test it with several representative datasets.