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JSON & Data Tools: Format, Validate, Convert, and Query JSON Without Code

A complete guide to browser-based JSON tools — format and validate JSON, generate TypeScript interfaces, convert to CSV or SQL, build Zod schemas, compare JSON diffs, and run JSONPath queries.

7 min read

Code editor showing JSON data structure

JSON is the universal language of APIs, configuration files, databases, and data interchange. Developers work with it constantly — and they constantly need to format it, validate it, transform it, or extract information from it. Here's a complete guide to the tools that handle every common JSON task, all running directly in your browser.

1. JSON Formatter & Validator

The most common JSON task: you paste a minified or raw API response and need to read it.

Our JSON Formatter does three things:

Pretty-print: Takes {"name":"Alice","age":30,"scores":[98,87,91]} and formats it as:

{
  "name": "Alice",
  "age": 30,
  "scores": [98, 87, 91]
}

Validate: Instantly flags syntax errors with the exact line and position. Common errors it catches:

  • Trailing commas (allowed in JS objects, invalid in JSON)
  • Single quotes instead of double quotes
  • Unquoted keys
  • Missing commas between fields
  • Mismatched brackets

Minify: Compress formatted JSON back to a single line for API requests or storage.

2. JSON to TypeScript: Auto-Generate Interfaces

Writing TypeScript interfaces by hand from a large API response is tedious and error-prone. Our JSON to TypeScript converter generates them automatically.

Input:

{
  "user": {
    "id": 1,
    "name": "Alice",
    "email": "alice@example.com",
    "roles": ["admin", "editor"],
    "metadata": {
      "createdAt": "2024-01-15T10:00:00Z",
      "active": true
    }
  }
}

Output:

interface Metadata {
  createdAt: string;
  active: boolean;
}

interface User {
  id: number;
  name: string;
  email: string;
  roles: string[];
  metadata: Metadata;
}

interface Root {
  user: User;
}

The converter handles nested objects, arrays, optional fields (if some keys are missing in the input), and union types. Paste a real API response and get production-ready TypeScript in seconds.

3. JSON to Zod Schema: Runtime Validation

TypeScript interfaces are compile-time only. For runtime validation — validating API responses, form data, or config files at runtime — you need Zod. Our JSON to Zod converter generates a complete Zod schema from any JSON.

From the same input above:

import { z } from "zod";

const MetadataSchema = z.object({
  createdAt: z.string().datetime(),
  active: z.boolean(),
});

const UserSchema = z.object({
  id: z.number(),
  name: z.string(),
  email: z.string().email(),
  roles: z.array(z.string()),
  metadata: MetadataSchema,
});

const RootSchema = z.object({
  user: UserSchema,
});

Notice the smart type inference — createdAt is recognized as an ISO datetime string, email is detected as an email address. These aren't just z.string() — they're validated formats.

4. JSON Schema Validator: Validate Data Against a Schema

If you have a JSON Schema (Draft 4, 6, 7, or 2019-09) and need to validate data against it, our JSON Schema Validator runs the validation in the browser using the ajv library.

Use cases:

  • Validate API request/response payloads during development
  • Test that generated data matches your schema
  • Debug schema validation errors before deploying
  • Verify configuration files conform to spec

The validator shows detailed error paths — not just "validation failed" but exactly which field failed and why:

/user/email: must match format "email"
/user/age: must be >= 0
/user/roles/2: must be string

5. JSON Diff Viewer: See Exactly What Changed

When debugging API changes or comparing two data snapshots, our JSON Diff Viewer shows exactly what was added, removed, or modified.

Left (before):            Right (after):
{                         {
  "status": "active",       "status": "inactive",   ← changed
  "count": 42,              "count": 42,
  "tags": ["a", "b"],       "tags": ["a", "b", "c"] ← added "c"
  "deprecated": true        
}                         }                         ← removed "deprecated"

The diff is shown in a tree view with color coding:

  • 🟢 Green: added
  • 🔴 Red: removed
  • 🟡 Yellow: modified
  • ⬜ Gray: unchanged

Common use cases:

  • Compare two API responses before and after a code change
  • Check what changed in a large configuration file
  • Debug why a cached response differs from a fresh one
  • Verify a data migration produced the expected output

6. JSONPath Finder: Click to Get the Path

JSONPath is the query language for JSON — equivalent to XPath for XML. When you need the JSONPath to a specific nested value, our JSON Path Finder lets you click any value in the tree and instantly shows the path.

{
  "store": {
    "books": [
      { "title": "Clean Code", "price": 29.99 },
      { "title": "The Pragmatic Programmer", "price": 39.99 }
    ]
  }
}

Click on 29.99 → Path: $.store.books[0].price Click on "The Pragmatic Programmer" → Path: $.store.books[1].title

Paths are shown in both dot notation ($.store.books[0].price) and bracket notation ($['store']['books'][0]['price']), making it easy to use in JavaScript, Python, or any JSONPath library.

7. JSON to CSV / CSV to JSON: Convert Between Formats

APIs return JSON; spreadsheets expect CSV. Our CSV ↔ JSON Converter handles both directions.

JSON array → CSV:

[
  { "name": "Alice", "age": 30, "city": "NYC" },
  { "name": "Bob", "age": 25, "city": "LA" }
]

Becomes:

name,age,city
Alice,30,NYC
Bob,25,LA

CSV → JSON: The reverse — takes a CSV with headers and produces an array of objects. Handles quoted fields, commas within values, and various line endings.

For more power over CSV data, use our SQL on CSV tool to run SELECT queries directly on uploaded CSV files — filtering, sorting, and joining without writing a line of Python.

8. JSON to SQL: Generate INSERT Statements

When populating a database with JSON data, our JSON to SQL Converter generates INSERT statements for any SQL dialect.

Input:

[
  { "id": 1, "name": "Alice", "email": "alice@example.com" },
  { "id": 2, "name": "Bob", "email": "bob@example.com" }
]

Output (PostgreSQL):

INSERT INTO users (id, name, email) VALUES
(1, 'Alice', 'alice@example.com'),
(2, 'Bob', 'bob@example.com');

Supports MySQL, PostgreSQL, SQLite, and SQL Server dialects — handling quoting styles, NULL values, and boolean representation correctly for each.

9. JSON Table Viewer: Spreadsheet View of JSON Arrays

Sometimes you don't need to write a query — you just want to see your JSON array as a table. Our JSON Table Viewer renders any JSON array of objects as a sortable, searchable table.

Click a column header to sort. Type in the search box to filter rows. Works with arrays of any size, handles nested objects by flattening them, and highlights matched search terms.

Quick Reference

Task Tool
Format/validate JSON JSON Formatter
Generate TypeScript interfaces JSON to TypeScript
Generate Zod validation schema JSON to Zod
Validate against JSON Schema JSON Schema Validator
Compare two JSON objects JSON Diff Viewer
Find a value's JSONPath JSON Path Finder
Convert JSON ↔ CSV CSV ↔ JSON Converter
Generate SQL INSERT statements JSON to SQL
View JSON as a table JSON Table Viewer

The through-line: all of these tools run entirely in your browser. Large JSON payloads never leave your machine, making them safe to use with production data, API keys embedded in responses, and any sensitive payload you wouldn't want processed by a third-party server.

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