JSON to Zod Schema Generator
Paste JSON and instantly generate a typed Zod schema with a z.infer type export — entirely in your browser.
- Runs in your browser
- No upload, no tracking
- Free forever
How it works
A JSON-to-Zod generator reads a sample JSON payload and emits a matching Zod schema — a runtime validator that checks the shape of data and, via z.infer, produces a static TypeScript type to match. This tool runs entirely client-side, so your JSON never leaves the page. It is built by JusDB, a managed database operations team, for validating the API responses and config that flow in and out of every database.
- 1
Paste your JSON
Drop a representative object into the input panel, or click Sample to load an example. The schema regenerates as you edit.
- 2
Name the schema
Set the Schema name field (default User); the exported constant and its inferred z.infer type are named from it.
- 3
Toggle strict mode
Turn Strict mode on to append .strict() so unknown keys are rejected and emit z.number().int() for integers, or leave it off for a more permissive schema.
- 4
Copy the schema
The output includes the import, the schema constant and the inferred type. Copy it with one click — nothing is uploaded.
Frequently asked questions
- Is my JSON kept private?
- Yes. The Zod schema is generated locally in your browser with JavaScript. Your JSON never leaves the page.
- Does it export a TypeScript type?
- Yes. The output includes the import statement, the exported schema constant, and an inferred type using z.infer<typeof schema> so you get end-to-end type safety.
- What does strict mode do?
- Strict mode appends .strict() to objects so unknown keys are rejected, and emits z.number().int() for integer values. Leave it off for more permissive schemas.
- Does it handle nested objects and arrays?
- Yes. Nested objects become nested z.object() schemas and arrays become z.array(...) with the item type inferred from the first element.
- What is the difference between a Zod schema and a TypeScript interface?
- A TypeScript interface is erased at compile time and cannot check data at runtime. A Zod schema validates the actual value at runtime — and z.infer gives you a matching static type — so it is the right choice for parsing untrusted API or form input.
- Can I name the schema?
- Yes. Set the Schema name field (default User) and the exported constant and its inferred type are named from it. The schema is generated locally in your browser, so nothing is uploaded.
From JSON sample to a runtime guard you can trust
TypeScript types are erased the moment your code compiles. They tell the editor what a value should look like, but at runtime there is nothing left to check the JSON that actually arrived over the wire. Zod closes that gap: it describes a shape as a real value that runs, so the data is verified the instant it crosses into your program. A generated schema turns one representative payload into that guard in seconds.
One schema, one source of truth
The killer feature is z.infer. Write the schema once, then derive the static type from it with type User = z.infer<typeof userSchema>. The validator and the type can never drift apart, because the type is computed from the validator. If you only need an erased compile-time shape with no runtime checking, the JSON to TypeScript interface generator is the lighter tool. Reach for Zod when the same shape also has to be enforced on live data.
Validate at every untrusted boundary
Anywhere data enters your program from outside, you are trusting a shape you did not produce: JSON bodies in API route handlers, submitted form fields, environment variables read at boot, third-party webhook payloads, and rows returned from a query. Parse each of these through a schema at the boundary and the rest of your code can assume the data is well-formed. A clear failure at the edge beats a confusing crash three layers deep.
parse versus safeParse
schema.parse(value) returns the typed value on success and throws a ZodError on failure — convenient inside a try/catch or a framework that maps thrown errors to responses. schema.safeParse(value) never throws; it returns a result object you branch on, checking >result.success before reading result.data or result.error. Prefer safeParse for user input you expect to be wrong sometimes, and parse where invalid data is genuinely exceptional.
Refine the generated schema
A generator can only see what one sample contains, so treat its output as a starting point. It cannot know that a status field is really an enum of fixed values, that an age must be a non-negative integer, that an email needs .email(), or that a field is optional rather than nullable — a key that may be absent (.optional()) is different from one that is present but null (.nullable()). Tighten strings with .min() / .max(), swap loose unions for z.enum(), and add format checks so the schema rejects the bad values the sample happened not to include. If you also publish the contract to non-TypeScript consumers, pair it with the JSON Schema generator.
The highest-value place to validate is just before a write. Run untrusted input through the schema before it reaches your database, and malformed or unexpected fields are rejected up front instead of being persisted and corrupting later reads.