Free JSON Schema Generator

The JSON Schema Generator is a free online tool that automatically creates JSON Schema definitions from sample JSON data for API validation and documentation.

Yes, it is completely free with no registration required. All schema generation happens client-side in your browser.

No, all processing happens locally in your browser. Your JSON data is never sent to any server.

Yes, the JSON Schema Generator is fully responsive and works on smartphones and tablets. You can use it on any device with a modern web browser -- no app download required.

No account or registration is needed. Simply open the JSON Schema Generator in your browser and start using it immediately. There are no sign-up walls or usage restrictions.

The JSON Schema Generator supports a wide range of popular formats and languages. Check the tool interface for the full list of supported options.

Simply enter your input in the provided field, adjust any settings to your preference, and the tool will process it instantly. You can then copy the result to your clipboard or download it.

The JSON Schema Generator works in all modern browsers including Chrome, Firefox, Safari, Edge, and Opera. For the best experience, use the latest version of your preferred browser.

JSON is the data itself — the actual object with real values, like a user record or an API response. JSON Schema is a separate document that describes the shape of that data: which fields exist, what type each one is (string, integer, boolean, array, object), which are required, and what values are allowed. Think of JSON as a filled-in form and JSON Schema as the blank template plus its rules. Validators read the schema to check whether any given JSON payload conforms before your code trusts it, which is how APIs catch malformed requests early. You write JSON by hand constantly, but writing the matching schema is tedious for nested data. This tool flips that around: paste a sample JSON object and it infers a complete schema for you to refine.

This generator targets four drafts, and the right one depends on your validator. Draft-07 is the recommended default for new projects — it is the most widely supported across libraries like Ajv, and it is what most tutorials assume. Pick Draft-04 only if you are working with older or legacy tooling that has not been updated. Draft-2019-09 introduced $defs and recursive references, while Draft-2020-12 is the latest and uses updated array keywords and $dynamicRef; choose these when your stack explicitly supports them or when you need their newer features. Changing the version here updates the $schema URL at the top of the output so your validator loads the correct rule set. If you are unsure, start with Draft-07 in the version selector and switch later if a tool complains.

By default this tool adds additionalProperties: false to every object, which tells a validator to reject any payload containing keys that were not in your sample. It is a deliberately strict starting point: it locks the contract to exactly the fields you provided, so unexpected or misspelled keys fail validation instead of slipping through silently. That is ideal for internal APIs where you want a tight, predictable shape. However, it can be too rigid for public or evolving APIs that may add optional fields over time — in those cases a new field would break clients using the strict schema. The fix is simple: delete that line or set it to true to permit extra properties. Generate your schema here, then relax additionalProperties on the objects where your API genuinely allows extension.

The generator lists every non-null key from your sample under the schema's required array, on the assumption that a field present in your example is expected to be present in real data. It also separates integer from number so whole numbers are typed precisely, and with format detection on it tags strings matching known patterns like email, uri, date-time, uuid, ipv4, and ipv6. The important caveat is that required fields reflect a single sample. If a key happens to be absent or null in one payload but optional in practice, the tool cannot know that from one example — so review the required list and remove any fields that are genuinely optional before shipping. Treat the output as a strong first draft. Paste your most complete representative sample to get the most accurate required-field inference from this tool.

Not without review. When you enable constraints, the tool seeds bounds inferred from your sample — minLength and maxLength for strings, minimum and maximum for numbers, and minItems, maxItems, and uniqueItems for arrays where the sample elements are all distinct. These are computed from one example, so they describe what your sample happened to contain, not the true business rules. For instance, if your sample username was eight characters, the maxLength might be set to eight even though longer names are valid, which would wrongly reject real data. Treat every generated constraint as a sensible default to tighten or loosen, never as a final rule. The stats badge showing property count and nesting depth helps you confirm the structure matches expectations. Generate the schema here, then adjust the bounds against your real data ranges before deploying it.