JSON Schema Validator
Validate JSON data against JSON Schema specifications. Ensure your data meets schema requirements with detailed error reporting, path-based validation feedback, and support for JSON Schema Draft-07 including formats, patterns, and complex validations.
Example Schemas
Recommended Settings
Validation Best Practices
- •Always validate JSON data against schemas before processing in production
- •Use specific data types and constraints (format, pattern, min/max) for better validation
- •Include 'required' fields to ensure critical data is always present
- •Use 'additionalProperties: false' to prevent unexpected fields
Schema Design Tips
- •Start with broad schemas and refine them based on real data
- •Use format validators (email, date-time, uri) for common patterns
- •Leverage arrays with 'items' schema for consistent list validation
- •Add descriptions to schema properties for better documentation
Pro Tips
- •Load example schemas to see common validation patterns in action
- •Paste both data and schema - tool auto-validates when both are valid JSON
- •Error messages show exact paths (e.g., '/user/email') to locate issues quickly
- •Supports JSON Schema Draft-07 including formats, patterns, and nested validations
Most Popular
Most users validate API responses and use format validators for emails, URLs, and dates
When to Use This Tool
Validate API request and response payloads against defined schemas during development and testing. Ensure incoming data meets requirements before processing, catching type errors, missing fields, and invalid formats early in the development cycle.
Verify data quality in ETL pipelines, data migrations, or imports. Use JSON Schema to define expected data structures and validate batches of data to identify quality issues, inconsistencies, or malformed records before they enter your system.
Validate configuration files, settings, or user inputs against schemas to prevent runtime errors. Ensure configuration data has correct types, required fields, and valid values before your application uses them.
Implement schema-based contract testing between microservices or frontend/backend integrations. Define and validate data contracts to ensure services communicate with compatible data structures, preventing integration failures.
How It Works
Paste your JSON data in the left panel and JSON Schema in the right panel
Or click an example schema button to load a pre-configured schema with sample data
Click 'Validate' or paste data - tool auto-validates when both inputs are valid JSON
View validation results with success/error status and detailed error messages
Errors show exact JSON paths (e.g., '/user/email') and validation rules that failed
Fix data or schema based on error feedback and re-validate instantly
All validation happens in your browser using industry-standard AJV library - your data never leaves your device
100% Private
Files never leave your device. All processing happens locally in your browser.
Lightning Fast
Powered by Pure JavaScript for optimal performance on modern browsers.
Secure
No data collection, no tracking, no sign-up required.
Frequently Asked Questions
What is JSON Schema validation?
JSON Schema validation checks if your JSON data conforms to a defined schema specification. The schema describes expected data types, required fields, value constraints (min/max, patterns), and structure. This ensures data quality and catches errors before they cause problems in your application.
Which JSON Schema version is supported?
This validator supports JSON Schema Draft-07, which is widely used and includes support for formats (email, date-time, uri), patterns (regex), numeric constraints (minimum, maximum), string constraints (minLength, maxLength), array validations, and nested object schemas.
What do the error paths mean?
Error paths use JSON Pointer notation (e.g., '/user/email' or '/items/0/name'). The path shows exactly where in your JSON data the validation failed. '/' means the root level, '/user/email' means the email property inside the user object, and '/items/0' means the first item in the items array.
Can I validate nested objects and arrays?
Yes! JSON Schema supports complex nested structures. Define schemas for nested objects using the 'properties' keyword, and for arrays use the 'items' keyword to specify the schema each array element must match. The validator will check all levels of nesting.
What validation rules are available?
JSON Schema supports many validations: type checking (string, number, boolean, object, array, null), required fields, numeric constraints (minimum, maximum, multipleOf), string constraints (minLength, maxLength, pattern), format validators (email, date, uri), array constraints (minItems, maxItems, uniqueItems), and more.
How do I use format validators?
Add a 'format' property to string fields in your schema. Common formats include 'email', 'date-time', 'date', 'time', 'uri', 'uuid', 'ipv4', and 'ipv6'. For example: {"type": "string", "format": "email"} will validate that the value is a properly formatted email address.
Is my data secure?
Yes, all validation happens entirely in your browser using the AJV (Another JSON Validator) library. Your JSON data and schemas are never sent to any server - everything stays on your device. This makes it safe to validate sensitive data, API keys, or confidential information.
What should I do if validation fails?
Review the error messages which show the exact path and rule that failed. Common issues include: wrong data types, missing required fields, values outside min/max ranges, strings not matching patterns, or invalid formats. Fix either your data to match the schema, or update the schema if your data structure is correct.