JSON Schema Generator
Paste any JSON and instantly generate a valid JSON Schema (Draft-07). Use it for LLM structured outputs, API validation, Zod schemas, Pydantic models, or form validation.
Schema will appear here…Use cases: OpenAI structured outputs (response_format), Zod/Yup validation, Pydantic models, API documentation.
Nested objects, arrays of objects, null types, and mixed arrays are all supported.
How to use
- 1 Paste a sample JSON object in the left panel. This serves as the data shape you want to describe.
- 2 Toggle the options: "Mark all properties as required" forces every key into the required array; "additionalProperties: false" rejects extra keys; "Include examples" embeds example values.
- 3 The JSON Schema (Draft-07) is generated instantly on the right as you type or change options.
- 4 Copy the schema with the "Copy" button and use it directly in OpenAI structured outputs, Zod/Yup validation, Pydantic models, or API documentation.
- 5 Click "Load example" to see a complex nested example with multiple data types.
Key features
- Generates JSON Schema Draft-07 from any JSON object instantly
- Auto-detects string formats: email, date-time, URI, UUID
- Handles nested objects, arrays of objects, and null types
- Options: mark all fields as required, block extra properties, include examples
- Compatible with OpenAI structured outputs, Zod, Yup, Pydantic, and JSON Schema validators
What Is a JSON Schema Generator?
JSON Schema is a declarative language for describing the structure of JSON data. It defines which fields are expected, what types they must be, which are required, and what constraints apply (min/max lengths, allowed values, format patterns, etc.). A JSON Schema Generator takes a sample JSON object and infers the corresponding schema automatically — saving you from writing the schema manually.
JSON Schema (Draft-07) is widely used across the industry: API validation (OpenAPI 3.0 uses JSON Schema), LLM structured outputs (OpenAI's response_format accepts JSON Schema), form validation (Zod, Yup, VeeValidate), and data contracts between services. This tool generates Draft-07-compliant schemas that work with all these ecosystems.
Common Use Cases
LLM structured outputs
Generate JSON schemas for OpenAI structured outputs (response_format) and function calling. The schema tells the LLM exactly what shape of data to produce.
Form validation (Zod, Yup, VeeValidate)
Use the inferred schema as a blueprint for your validation libraries. The type mapping and constraints give you a head start when defining form validation rules.
API request/response validation
Define the expected shape of API payloads in OpenAPI specs or middleware validation. Validate incoming JSON against the schema to reject malformed requests early.
Pydantic models (Python)
Translate the generated schema into Pydantic BaseModel classes for your FastAPI or Django REST endpoints. The type mapping translates directly to Python types.
Data contracts between services
Define a schema for JSON messages exchanged between microservices. Both producer and consumer validate against the same schema for robust integration.
CI/CD data validation
Validate JSON configuration files and test fixtures against the schema in your CI pipeline using Ajv, catching data shape mismatches before they reach production.
JSON → JSON Schema Type Mapping
How each JSON value type is mapped to a JSON Schema type.
| JSON Value | Example | JSON Schema Type |
|---|---|---|
| string | "hello" | type: "string" |
| integer | 42 | type: "integer" |
| float | 3.14 | type: "number" |
| boolean | true | type: "boolean" |
| null | null | type: "null" |
| array | [1, 2, 3] | type: "array", items: { type: "integer" } |
| object | {"key": "val"} | type: "object", properties: {…} |
| email string | "user@example.com" | type: "string", format: "email" |
| URI string | "https://example.com" | type: "string", format: "uri" |
Frequently Asked Questions
How do I use the generated schema with OpenAI structured outputs?
OpenAI's response_format parameter accepts a JSON Schema object in the json_schema mode. Copy the schema generated by this tool and pass it as { "type": "json_schema", "json_schema": { "name": "...", "schema": yourSchema } }. Enable additionalProperties: false in the options for stricter validation.
Can I use the schema directly in Zod or Yup?
While Zod and Yup have their own DSLs, you can use the generated schema as a reference to build your validator. Tools like zod-to-json-schema and yup-to-json-schema work in reverse for exporting schemas. For direct validation, libraries like Ajv and @exodus/schemasafe consume JSON Schema natively.
Does it handle nested objects and arrays?
Yes. Nested objects generate nested properties with their own type: "object" definitions. Arrays of objects infer the schema from the first array element. Mixed-type arrays generate a oneOf with deduplicated options.
What JSON Schema version does this generate?
The tool generates Draft-07 schemas (indicated by the $schema property pointing to http://json-schema.org/draft-07/schema#). Draft-07 is the most widely adopted version — supported by OpenAI, OpenAPI 3.0, Ajv, and most validators. The core principles are the same across all drafts, so migrating to 2020-12 or other versions is straightforward.
Is my data sent to a server?
No. All processing happens in your browser. The JSON you paste and the generated schema never leave your machine. This is especially important when working with sensitive API responses, internal data structures, or proprietary schemas.