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JSON to Zod Schema (TypeScript) Generator — Free Online

Convert JSON to a Zod schema in TypeScript using z.object(), z.string(), z.number(), z.boolean(), and z.array() using AI. Free, no sign-up required.

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JSON to Zod Schema (TypeScript) Generator — Free Online

About JSON to Zod Schema (TypeScript) Generator — Free Online

JSON to Zod Schema converts a JSON object or array into a TypeScript-ready Zod schema using z.object(), z.string(), z.number(), z.boolean(), z.array(), and z.null() — instantly giving you runtime-validated type definitions. Developers use it to bootstrap form validation, API response parsing, and tRPC/Next.js data contracts without hand-writing repetitive schema boilerplate.

JSON Type to Zod Mapping Reference

JSON Value ExampleDetected TypeZod OutputNotes
"hello"stringz.string()Any quoted string value
42numberz.number()Integers and floats both map to z.number()
3.14numberz.number()No distinction between int and float in JSON
true / falsebooleanz.boolean()JSON boolean literals
nullnullz.null()Use .nullable() when mixed with other types
[1, 2, 3]array (uniform)z.array(z.number())Element type inferred from first item
["a", "b"]array (uniform)z.array(z.string())Homogeneous arrays get typed element schemas
[1, "a"]array (mixed)z.array(z.union([z.number(), z.string()]))Mixed arrays produce a union element type
{"key": ...}objectz.object({ key: ... })Nested objects become nested z.object() calls
undefined / missing keyoptionalz.optional()Keys absent in sample → mark optional manually

Zod vs Alternative Schema Libraries

FeatureZodYupJoiJSON Schema (AJV)
TypeScript-firstYes — infer<> built-inPartial (DefinitelyTyped)NoNo
Type inferencez.infer<typeof schema>InferType<typeof schema>ManualManual
Runtime parsingschema.parse() / safeParse()schema.validate()schema.validate()ajv.validate()
Nested objectsz.object() recursiveobject().shape()object().keys()$ref / nested
Array item typingz.array(z.string())array().of(string())array().items(Joi.string())items: { type: string }
Bundle size (min+gz)~14 KB~21 KB~25 KB~30 KB (AJV)
tRPC / Fastify integrationNativePlugin neededPlugin neededPlugin needed
Coercion supportz.coerce.number()Manual transformconvert: truecoerceTypes: true
Error formattingZodError with path[]ValidationErrorValidationErrorErrorObject[]
Browser compatibleYesYesYesYes

Frequently Asked Questions

How do I convert a JSON object to a Zod schema in TypeScript?

Paste your JSON into the tool and it generates a z.object() schema with correctly typed fields — z.string(), z.number(), z.boolean(), z.array(), or nested z.object() calls. Copy the output into your TypeScript file, import z from 'zod', and use schema.parse(data) or schema.safeParse(data) for runtime validation. For exact type inference, use type MyType = z.infer<typeof schema> directly below the schema definition.

Does Zod differentiate between integers and floats from JSON?

No — JSON has only one numeric type and Zod mirrors this with z.number() for all numeric values. If you need integer-only validation, chain .int() to get z.number().int(). For positive numbers use .positive(), for bounded ranges use .min(0).max(100).

How does the generator handle null values in JSON?

A field whose sample value is null is typed as z.null(). In practice most nullable API fields can hold a real value or null, so you should update the generated schema to z.string().nullable() (or whichever base type applies). The tool flags null fields so you can make this adjustment quickly.

Can I use the generated Zod schema with tRPC input validation?

Yes — tRPC accepts any Zod schema directly as the input option in a procedure definition: t.procedure.input(generatedSchema).query(...). This gives you end-to-end type safety from the API boundary through to your React components with no extra glue code. Just ensure you are on tRPC v10+ and zod v3.x for full compatibility.

What happens with arrays of mixed types in the JSON input?

When the generator detects an array whose elements have different types (e.g. [1, "two", true]), it produces z.array(z.union([z.number(), z.string(), z.boolean()])). Homogeneous arrays like [1, 2, 3] produce the cleaner z.array(z.number()). If your real data is always one type but the sample is mixed, edit the output to remove the union for stricter validation.

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