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JSON Schema Generator

Infer JSON Schema from sample JSON, optionally merge manual schema edits, and validate data against the active schema

Example Results

1 examples

Infer schema from API payload

Turn a sample response into a reusable JSON Schema and validate it immediately

{
  "summary": {
    "valid": true
  },
  "inferredSchema": {
    "type": "object"
  }
}
View input parameters
{ "sampleJson": "{\n \"id\": 101,\n \"email\": \"[email protected]\",\n \"roles\": [\n \"admin\",\n \"user\"\n ],\n \"profile\": {\n \"active\": true\n }\n}", "draft": "2020-12", "inferEnums": true, "detectFormats": true, "validateAdjustedSchema": true }

Key Facts

Category
Development
Input Types
textarea, select, checkbox
Output Type
json
Sample Coverage
4
API Ready
Yes

Overview

The JSON Schema Generator allows you to instantly derive a formal JSON Schema from any sample JSON object, enabling seamless API documentation and data structure validation.

When to Use

  • •When you need to generate documentation for a new API endpoint based on a sample response.
  • •When you want to enforce data consistency by validating incoming JSON payloads against a strict schema.
  • •When you need to convert unstructured JSON data into a reusable schema definition for your development workflow.

How It Works

  • •Paste your sample JSON into the input field to automatically infer the structure, types, and nested objects.
  • •Configure optional settings like format detection and enum inference to refine the generated schema.
  • •Optionally provide a manual schema adjustment to override specific fields or constraints.
  • •Run the validation check to ensure your sample data strictly adheres to the active schema definition.

Use Cases

Standardizing API response structures for frontend and backend integration.
Validating configuration files in data engineering pipelines to prevent runtime errors.
Creating reusable schema templates for microservices communication.

Examples

1. API Response Documentation

Backend Developer
Background
The team needs to document a new user profile API endpoint but lacks a formal schema definition.
Problem
Manually writing a schema for complex, nested user objects is error-prone and slow.
How to Use
Paste a sample API response into the 'Sample JSON' field and enable 'Detect Common Formats'.
Example Config
draft: 2020-12, detectFormats: true, inferEnums: true
Outcome
A complete JSON Schema is generated, correctly identifying email formats and nested object types.

2. Data Pipeline Validation

Data Engineer
Background
Incoming JSON logs from a third-party service must be validated before being ingested into the data warehouse.
Problem
Inconsistent data fields cause downstream ingestion failures.
How to Use
Generate a schema from a valid log sample, then use the 'Adjusted Schema JSON' field to add required field constraints.
Example Config
validateAdjustedSchema: true
Outcome
The tool confirms the sample log matches the strict schema, ensuring the pipeline will process the data correctly.

Try with Samples

json
Chat Transcript JSON Samples
JSON examples for multi-role chat transcripts
title token json
json
Rich Media JSON Samples
JSON examples for popular rich text editors (TipTap, Quill, Slate)
title token json
json
JSON Samples
JSON (JavaScript Object Notation) format examples from simple to complex structures
title token json
json
PDF Samples
Generated PDF samples from tools dated 2026-02-01 to 2026-02-10
preferred input family json
json

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FAQ

What JSON Schema drafts are supported?

The tool supports both the 2020-12 and Draft-07 specifications.

Can I manually edit the generated schema?

Yes, you can paste your modified schema into the 'Adjusted Schema JSON' field to override the auto-inferred version.

Does it support format detection?

Yes, when enabled, the tool automatically identifies common formats like email addresses or dates within your JSON.

What happens if my sample JSON is invalid?

The tool will alert you to syntax errors in your input JSON before attempting to generate a schema.

Is the validation performed locally?

Yes, the validation process runs against the active schema definition provided in the tool configuration.

API Documentation

Request Endpoint

POST /en/api/tools/json-schema-generator

Request Parameters

Parameter Name Type Required Description
sampleJson textarea Yes -
draft select No -
inferEnums checkbox No -
detectFormats checkbox No -
adjustedSchemaJson textarea No -
validateAdjustedSchema checkbox No -

Response Format

{
  "key": {...},
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}
JSON Data: JSON Data

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-json-schema-generator": {
      "name": "json-schema-generator",
      "description": "Infer JSON Schema from sample JSON, optionally merge manual schema edits, and validate data against the active schema",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=json-schema-generator",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

If you encounter any issues, please contact us at [email protected]