JSON to TypeScript Generator
Paste JSON and instantly generate typed TypeScript interfaces — entirely in your browser. Your payloads never leave the page.
- Runs in your browser
- No upload, no tracking
- Free forever
How it works
A JSON-to-TypeScript generator reads a sample JSON payload and emits matching TypeScript interfaces, inferring the type of each field and giving nested objects and arrays their own named interfaces. This tool runs entirely client-side, so proprietary payloads never leave the page. It is built by JusDB, a managed database operations team, for the everyday job of turning API responses and query results into typed application code.
- 1
Paste a JSON sample
Drop a representative object or array into the input panel, or click Sample to load an example. Interfaces regenerate instantly as you type.
- 2
Name the root
Set the Root name in the toolbar — every interface name is derived from it and from your JSON keys in PascalCase.
- 3
Review the types
Nested objects become their own interfaces, arrays of objects produce an Item interface, mixed arrays become unions, and invalid JSON is flagged inline.
- 4
Copy or download
Copy the result to your clipboard or download it as a types.ts file. Nothing is ever uploaded.
Frequently asked questions
- Is my JSON sent to a server?
- No. Parsing and interface generation run entirely in your browser with JavaScript. Your JSON never leaves the page, so it is safe for proprietary payloads.
- How does it handle nested objects and arrays?
- Nested objects become their own named interfaces, and arrays of objects produce an Item interface that is referenced by the parent. Mixed-type arrays are emitted as union types.
- Can I rename the root interface?
- Yes. Set the root name in the toolbar and every generated interface name is derived from it and from your JSON keys using PascalCase.
- What happens with empty arrays or objects?
- Empty arrays become unknown[] and empty objects become Record<string, unknown>, so the output stays type-safe even when the sample data is incomplete.
- What is the difference between an interface and a Zod schema?
- An interface is a compile-time-only type with no runtime cost — it cannot validate data at runtime. A Zod schema validates the shape at runtime and infers a matching type. Use this tool for plain types; use the JSON to Zod tool when you need runtime validation.
- Can I download the generated types?
- Yes. Use the download button to save the output as a types.ts file, or copy it to the clipboard with one click. Everything is generated in your browser, so nothing is uploaded.
From JSON payloads to typed TypeScript
The fastest way to type an unfamiliar API is to capture one real response and let a generator sketch the shape for you. That sketch is a starting point, not a finished contract — the sections below cover what inference can and cannot recover from a single sample, and how to harden the result before it ships.
Interface or type alias?
For an object describing an API entity, an interface is usually the better default: it reads cleanly, supports declaration merging, and produces friendlier error messages and tooltips. Reach for a type alias when you need something an interface cannot express — union types, intersections, mapped or conditional types, or tuples. A common pattern is an interface for each entity plus a few type aliases for the unions that tie them together, such as type Status = "active" | "archived".
What a single sample cannot tell you
Inference only sees the bytes in front of it, so a generated type is a draft to refine. One response cannot reveal which fields are optional versus always present, so a key that simply happened to be absent gets dropped rather than marked with ?. It cannot distinguish an explicit null from a missing key, collapse repeated string values into an enum or a literal union, or know that a field which arrived as 0 is sometimes a float, sometimes a string id, or sometimes one of several object shapes. Feed it the richest example you have, then widen the output by hand: add ? for optionals, union in null where the API truly returns it, and replace open string fields with literal unions for known sets of values.
Types are erased — validate at runtime
TypeScript types are compile-time only; they are stripped out before the code runs, so they cannot catch a malformed response in production. The compiler will happily trust that res.json() matches your interface even when the server sends back something else. When the data crosses a trust boundary — a third-party API, a webhook, a form payload — pair the generated type with a runtime validator. A schema library such as Zod parses incoming data and infers the matching static type from one source of truth, while io-ts offers a similar codec-based approach. If you instead need a language-neutral contract for documentation or cross-service validation, generate JSON Schema from the same payload.
Naming and nesting
Readable types come from deliberate naming. Give the root interface the name of the entity it models rather than a generic Root, and let nested objects become their own named interfaces so they can be imported and reused elsewhere. For deeply nested or array-heavy payloads, consider flattening a level or two and referencing extracted interfaces by name — a wall of inline anonymous objects is technically correct but hard to read, diff, and document.
Generate the draft here, then commit the type next to a runtime validator built from the same sample so your compile-time and runtime contracts never drift apart.