JSON to TypeScript & JSON Schema Generator | Free Online Tool

A JSON to TypeScript generator takes a JSON sample and infers types you can paste into a codebase (interfaces or type aliases). A JSON Schema generator produces an inferred schema you can use as a starting point for validation and documentation. This tool runs locally in your browser, which is useful when your sample JSON includes internal IDs or customer data.

1. Paste valid JSON: If you copied from logs, consider formatting it first so it’s easier to inspect.
2. Choose output: Generate TypeScript, JSON Schema, or both, and set a root type name like ApiResponse.
3. Copy the result: Paste into your project, then refine constraints (enums, patterns, min/max) if needed.

• Faster integration: Get a typed starting point for an API response in seconds.
• More consistent payloads: Share the same inferred shape across teams (frontend, backend, QA).
• A practical baseline for validation: JSON Schema output is a good first draft for runtime checks and docs.

Use case 1: Typing an API response in a frontend app

If you’re integrating a new endpoint, paste the JSON response, generate UserProfileResponse, and immediately get autocomplete and type checking in your UI code.

Use case 2: Documenting payloads in a backend service

Generate a schema draft from a real sample, then tighten it with required fields, enums, and formats so downstream consumers know what to expect.

Use case 3: Handling “messy” arrays with optional fields

When you paste an array of objects where not every object has the same keys, this tool marks missing keys as optional in TypeScript—useful for real‑world logs and partial responses.

Basic example (object → interface)

Input:

{
  "id": "usr_123",
  "email": "sarah.connor@example.com",
  "isActive": true,
  "createdAt": "2025-12-01T10:15:00Z"
}

Output (TypeScript, example):

export interface Root {
  createdAt: string;
  email: string;
  id: string;
  isActive: boolean;
}

Advanced example (array → optional fields + unions)

Input:

[
  { "id": "evt_1", "type": "click", "meta": { "x": 12, "y": 9 } },
  { "id": "evt_2", "type": "purchase", "meta": { "total": 19.99 }, "coupon": null }
]

Output (TypeScript, example):

export interface RootItemMeta {
  total?: number;
  x?: number;
  y?: number;
}

export interface RootItem {
  coupon?: null;
  id: string;
  meta: RootItemMeta;
  type: string;
}

export type Root = RootItem[];

In this sample, coupon only appears in one object, so it becomes optional. The meta object also becomes a merged shape where keys can be optional based on what appears across the array.

“Invalid JSON: …”

This generator requires strict JSON:

• Keys must be quoted ("id", not id).
• No trailing commas.
• Strings must use double quotes.

If you copied from a JavaScript object or a log format, run it through the JSON formatter to surface the exact parse error.

“It generated unknown[] for my array”

An empty array ([]) doesn’t contain enough information to infer item types. Add a representative sample item to your JSON, regenerate, and then remove the sample if necessary.

“The schema is too permissive”

Inferred JSON Schema is a starting point. Real production schemas usually need constraints like:

• enums ("status": "active" | "disabled")
• patterns (IDs, slugs)
• min/max values
• required vs optional rules that match your API contract

• Use real samples: The more representative your sample is, the closer the inferred types will be to production reality.
• Format and then type: Use the JSON formatter first, then generate types, then run the TypeScript output through the TypeScript formatter for clean diffs.
• Generate from multiple events: If your API returns a list of events with different shapes, paste a few items into the array so optional fields and unions appear in the output.

• Fix parsing errors with the JSON formatter and compress payloads with the JSON minifier.
• Keep generated code consistent with the TypeScript formatter.
• If your “JSON” is really YAML, convert it first using the YAML formatter.

Generation happens locally in your browser. This matters because JSON samples often include customer emails, internal IDs, or debug fields you shouldn’t upload to third‑party services. Treat inferred output as a draft: validate it against real API behavior and update it when your payload evolves.