JSON Schema Validator
Validate, test, and automatically generate standard JSON Schemas with real-time error diagnostics and live linting.
What is JSON Schema?
JSON Schema is an IETF declarative standard for annotating and validating JSON documents. It ensures API contracts, configuration files, and data pipelines adhere to expected types, required fields, and boundary constraints.
- API Request Guards: Filter out invalid payloads before business logic execution.
- Live Type Safety: Enforce strict strings, numbers, booleans, and enums.
- Self-Documenting: Serves as an interactive OpenAPI/Swagger compatible contract.
Schema Cheatsheet
{"type": "string", "format": "email", "minLength": 3}
{"type": "number", "minimum": 0, "maximum": 100}
{"type": "object", "required": ["id", "email"]}
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WebToolar JSON Schema Validator & Generator is a free online tool that validates JSON data against a schema, infers a schema from sample data, and generates mock data from an existing schema, all in one place. Everything runs in your browser, so nothing you paste is uploaded or stored.
What Is a JSON Schema Validator?
A JSON Schema validator checks whether a JSON document follows a set of rules you define, things like required fields, allowed data types, string patterns, or number ranges. Instead of manually reading through a payload to spot a missing field or a wrong type, you write the rules once as a schema and the tool checks any JSON document against it instantly, flagging exactly which property failed and why.
It is built for backend developers testing API responses, frontend teams validating form payloads before submission, and anyone documenting the shape of a JSON contract shared between systems.
Example: Validating a User Profile
Say you have this schema requiring an id, username, email, and role:
{
"type": "object",
"properties": {
"id": { "type": "integer" },
"email": { "type": "string", "format": "email" },
"role": { "type": "string", "enum": ["admin", "editor", "guest"] }
},
"required": ["id", "email", "role"]
}
Paste in a data sample missing the email field, click Validate JSON Against Schema, and the tool reports the exact issue, Missing required property "email", instead of a generic failure. Fix the payload and revalidate in seconds.
Which Mode Should You Use?
| Mode | Best For | Example Input |
|---|---|---|
| Validate JSON | Checking a JSON payload against an existing schema before it goes into production | A schema plus a sample API response |
| Generate Schema | Creating a schema from real data when none exists yet | A JSON response with no formal schema |
| Mock Data | Producing a realistic sample payload from a schema for testing or documentation | A finished schema, no data yet |
How to Validate JSON Online (Step by Step)
- Paste your JSON Schema into the left editor, or pick a template like User Profile or E-Commerce Product to start faster.
- Paste the JSON data you want to check into the right editor.
- Click Validate JSON Against Schema.
- Review the pass or fail result. Failed checks list the exact property path and the rule that was broken.
- Fix the data or the schema and validate again until it passes.
Key Features
- Validate JSON data against a schema with detailed, path level error messages
- Infer a schema automatically from sample data
- Generate mock data straight from a schema for testing or documentation
- Six ready made templates covering common shapes like user profiles, products, and auth tokens
- Format and minify both the schema and the data independently
- Upload schema or data files directly, or export results as JSON
- Runs entirely in your browser, no data is uploaded or stored
Where This Tool Is Useful
- Testing API responses: paste a real response and your schema to confirm the contract still holds after a backend change.
- Documenting an undocumented API: use Generate Schema on a sample response to get a starting schema you can refine and share with your team.
- Preparing test data: use Mock Data to produce realistic sample payloads for frontend development before the real API is ready.
- Cleaning up messy JSON before validating: unescape or reformat a JSON string first with the JSON Escape / Unescape tool if your data arrived as an escaped string.
- Inspecting a large payload: drop your validated JSON into the JSON Tree Viewer to explore nested objects and arrays visually.
FAQs
What JSON Schema versions does this tool support?
The validator works with Draft-07 style schemas, the most widely used version, covering type, required, enum, pattern, minimum, maximum, and nested object and array rules.
Can I generate a schema from an array of objects?
Yes. Paste an array as your sample data and use Generate Schema. The tool infers the item structure from the first element and applies it as the array’s item schema.
Why does validation fail even though my JSON looks correct?
The most common cause is a missing required property, a type mismatch such as a number stored as a string, or an extra property when additionalProperties is set to false in the schema. The error list shows the exact path and rule that failed.
Is mock data generated randomly?
Mock data follows the types and formats defined in your schema, such as valid emails or ISO dates, but values are representative placeholders rather than randomized every time. Use it as a structural starting point, not real test coverage.
Can I validate deeply nested JSON objects?
Yes. The validator recurses through nested objects and arrays and reports the full property path for any nested field that fails a rule.
Is my schema or data uploaded anywhere?
No. Validation, schema generation, and mock data creation all run locally in your browser. Nothing is sent to or stored on our servers.