JSON to TypeScript Converter

The JSON to TypeScript Converter turns a sample JSON payload into a set of clean, ready-to-use TypeScript interfaces. You paste an object or array, and the tool walks every field, infers the correct type for each value, and emits an interface for the top-level shape plus a separate interface for every nested object it finds. That saves you from hand-writing types for an API response and keeps your front-end code honest about the data it consumes.

Type inference covers the primitives you expect, mapping strings to string, numbers to number, and booleans to boolean, while nested objects become their own named interfaces and arrays become element-typed arrays such as User[]. Empty arrays and explicit nulls fall back to a safe any, so the generated code always compiles even when your sample is incomplete. You can set the root interface name and optionally mark every property readonly.

Everything runs locally in your browser, so the JSON you paste is never uploaded or logged. That makes the converter safe for real API responses, staging data, or anything containing internal field names you would rather not share. Because it is instant and free, you can iterate on a payload, tweak the sample, and regenerate the types as many times as you need without any accounts or limits.

Features

• Generates a named interface for the root shape and a separate interface for every nested object.
• Infers string, number, boolean, array and object types from the values in your sample JSON.
• Names array element types using a singularized version of the property name for readable output.
• Lets you set the root interface name so the generated types fit your existing code style.
• Optional readonly modifier marks every property immutable for safer, more predictable models.
• Quotes property names that are not valid identifiers so the output always compiles cleanly.
• Runs entirely in your browser with instant results and copy or download of the finished code.

How to use JSON to TypeScript Converter

1. Paste a representative JSON object or array into the input box.
2. Set the root interface name to match the model you are creating.
3. Toggle the readonly option if you want every property to be immutable.
4. Read the generated interfaces in the output panel and check the inferred types.
5. Copy the code into your project, or download it as a TypeScript file.
6. Adjust your sample JSON and regenerate if a field type needs refining.

Benefits

• Front-end developers get accurate types for API responses without writing them by hand.
• Teams keep client and server models aligned by generating interfaces from real payloads.
• Code reviewers spot shape mismatches faster when responses are strongly typed.
• Newcomers learn a codebase quicker by seeing the exact structure of the data it handles.
• TypeScript catches typos and missing fields at compile time instead of at runtime.
• Because conversion is local, private API payloads never leave your machine.

Type inference is based on the specific sample you provide, so the more representative your JSON is, the better the results. For arrays, the converter inspects the first element to decide the element type, which works well when a list is homogeneous. If a property can be null or missing in some responses, review the generated type and widen it manually, for example by adding a union with null or marking the property optional with a question mark.

The tool intentionally keeps output simple and predictable rather than trying to detect every possible union. This makes the generated interfaces easy to read and edit, which is usually what you want as a starting point. You remain in control of the final types, so you can rename interfaces, extract shared shapes, or add JSDoc comments after pasting the code into your editor.

All processing happens in your browser using JavaScript, so nothing is transmitted anywhere and there is no size limit beyond your device memory. That means you can safely paste large, real-world responses that include internal identifiers or business data, generate types, and move on without worrying about where the sample went.