TypeScript to Zod Schema Generator: Convert Interfaces to Runtime Validation

TypeScript gives you compile-time type safety. Zod gives you runtime validation with the same type ergonomics. The missing link is converting your existing TypeScript interfaces into Zod schemas — manually rewriting every field is tedious and error-prone.

Convert TypeScript to Zod →

The Problem TypeScript Can’t Solve Alone

TypeScript types exist only in your editor and at compile time. Once the code is transpiled and running, the types are gone. An API response typed as User is still just unknown at runtime — TypeScript trusts you, it doesn’t verify.

Consider this:

interface User {
  id: number
  name: string
  role: 'admin' | 'user' | 'guest'
  email?: string
}

// TypeScript accepts this — but the cast is a lie
const user = response.data as User
console.log(user.role.toUpperCase()) // may throw at runtime if role is missing or wrong type

Zod solves this by validating at the boundary where untrusted data enters your system.

How TypeScript-to-Zod Conversion Works

The tool parses your TypeScript interface and type declarations and generates equivalent Zod schema code.

Input:

interface Address {
  street: string
  city: string
  zipCode?: string
}

export interface User {
  id: number
  name: string
  role: 'admin' | 'user' | 'guest'
  age?: number
  isActive: boolean
  tags: string[]
  address: Address
}

export type Status = 'active' | 'inactive' | 'pending'

Output:

import { z } from 'zod'

export const AddressSchema = z.object({
  street: z.string(),
  city: z.string(),
  zipCode: z.string().optional(),
})
export type Address = z.infer<typeof AddressSchema>

export const UserSchema = z.object({
  id: z.number(),
  name: z.string(),
  role: z.enum(['admin', 'user', 'guest']),
  age: z.number().optional(),
  isActive: z.boolean(),
  tags: z.array(z.string()),
  address: AddressSchema,
})
export type User = z.infer<typeof UserSchema>

export const StatusSchema = z.enum(['active', 'inactive', 'pending'])
export type Status = z.infer<typeof StatusSchema>

Note that cross-references are handled automatically: Address inside User becomes AddressSchema in the output. The z.infer<> exports give you TypeScript types derived from the schemas — so you can delete your original interfaces once you’ve added constraints.

Supported TypeScript Constructs

TypeScript	Zod
string	z.string()
number	z.number()
boolean	z.boolean()
null	z.null()
undefined	z.undefined()
any / unknown	z.unknown()
prop?: T	.optional()
A | B	z.union([A, B])
'a' | 'b' | 'c'	z.enum(['a', 'b', 'c'])
T[] / Array<T>	z.array(T)
{ key: T }	z.object({ key: T })
A & B	z.intersection(A, B)
[A, B]	z.tuple([A, B])
Partial<T>	.partial()
Record<K, V>	z.record(K, V)

After Conversion: Adding Constraints the Generator Can’t Infer

The generator creates structurally correct schemas, but JSON types don’t carry semantic constraints. A TypeScript string field might actually need to be an email, a URL, or have a minimum length. Add these after generating:

// Generated
email: z.string()
age: z.number()
password: z.string()

// After refinement
email: z.string().email()
age: z.number().int().min(0).max(150)
password: z.string().min(8).max(128)

String formats Zod supports out of the box:

• .email() — validates email format
• .url() — validates URL format
• .uuid() — validates UUID format
• .datetime() — validates ISO 8601 datetime
• .ip() — validates IPv4 or IPv6

Practical Workflow: TypeScript First, Then Zod

If you already have TypeScript interfaces throughout your codebase, migrating to Zod doesn’t require rewriting everything at once. Use this incremental approach:

1. Identify your boundaries — API response parsing, form submission handlers, environment variable loading
2. Generate schemas for those boundary types using the tool
3. Wrap boundary parsing with schema.safeParse() or schema.parse()
4. Delete duplicate as TypeName casts — replace them with properly validated data

// Before: implicit trust
async function getUser(id: string): Promise<User> {
  const res = await fetch(`/api/users/${id}`)
  return res.json() as User
}

// After: runtime validation
const UserSchema = z.object({
  id: z.string().uuid(),
  name: z.string().min(1),
  role: z.enum(['admin', 'user', 'guest']),
  email: z.string().email().optional(),
})

async function getUser(id: string) {
  const res = await fetch(`/api/users/${id}`)
  return UserSchema.parse(await res.json())
}

Handling null vs optional in Generated Schemas

TypeScript distinguishes between three nullable states:

interface Example {
  required: string        // must be present and a string
  optional?: string       // may be absent (undefined)
  nullable: string | null // present but may be null
  nullish?: string | null // may be absent OR null
}

The generator maps these correctly:

const ExampleSchema = z.object({
  required: z.string(),
  optional: z.string().optional(),
  nullable: z.union([z.string(), z.null()]),
  nullish: z.string().nullish(),
})

In Zod v3, you can also write z.string().nullable() for string | null — both are equivalent.

Using Schemas for More Than Parsing

Once you have Zod schemas, they can do more than just parse data:

// Generate mock data (with zod-mock or @anatine/zod-mock)
import { generateMock } from '@anatine/zod-mock'
const mockUser = generateMock(UserSchema)

// Generate JSON Schema for OpenAPI docs (with zod-to-json-schema)
import { zodToJsonSchema } from 'zod-to-json-schema'
const jsonSchema = zodToJsonSchema(UserSchema, 'UserSchema')

// Transform data during parsing
const UserSchema = z.object({
  name: z.string().transform(s => s.trim()),
  createdAt: z.string().datetime().transform(s => new Date(s)),
})

Related Tools

• JSON to Zod → — generate schemas from JSON data samples (when you have data, not types)
• JSON to TypeScript → — generate TypeScript interfaces from JSON (the reverse direction)

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