JSON Validator

What is a JSON validator?

A JSON validator checks whether a piece of text is syntactically correct JSON according to the official specification, RFC 8259. When the document is valid, you get a clear confirmation along with a summary of what the document contains. When it is not, you get the thing that actually matters: the exact line and column where parsing failed, plus the parser's explanation of what it expected to find there.

This matters because JSON errors in the wild are usually silent and confusing. An application might log a vague Unexpected tokenmessage, a CI pipeline might fail with no context, or an API might reject your request body with a generic 400 error. Pasting the offending document into a validator turns minutes of squinting into an instant answer. Validation runs entirely in your browser with the JavaScript engine's native parser - the same strict parser used by Node.js and every modern browser - so the verdict you get here is the same verdict your production code will give.

How to use the JSON validator

1. Paste your JSON into the text area. It can come from an API response, a configuration file, a log line, or anywhere else. You can also click Load sample (invalid) to see how error reporting works.
2. Click Validate JSON. The result appears immediately below the button.
3. If the document is valid, a green banner confirms it and summarizes the top-level structure - for example, “an object with 4 keys” or “an array with 250 items”.
4. If the document is invalid, a red banner shows the line and column of the first error together with the parser's message. Go to that location in your source, fix the problem, paste the corrected version, and validate again.
5. Repeat until valid. Because parsers stop at the first violation, complex documents occasionally need two or three rounds.

Examples

Example 1: trailing comma

{
  "name": "Ada",
  "skills": ["math", "analysis",],
  "active": true
}

The comma after "analysis" makes this invalid. The validator reports an error at line 3 - JSON arrays and objects must not end with a trailing comma. Deleting that one character makes the document pass.

Example 2: single quotes

{'name': 'Ada'}

This is a valid JavaScript object literal but invalid JSON, which requires double quotes around both keys and string values: {"name": "Ada"}.

Example 3: valid document

{
  "service": "payments",
  "retries": 3,
  "endpoints": ["primary", "fallback"],
  "debug": null
}

This passes, and the validator summarizes it as an object with 4 keys.

JSON rules worth memorizing

Almost every validation failure traces back to one of a handful of rules where JSON is stricter than JavaScript:

• Strings and property names use double quotes only.
• No trailing commas after the last element of an array or object.
• No comments - JSON has no comment syntax at all.
• Numbers cannot have leading zeros (01), a leading plus sign, or be NaN / Infinity.
• The only literals are true, false, and null - all lowercase. undefined does not exist in JSON.
• Inside strings, double quotes, backslashes, and control characters must be escaped (\", \\, \n).

Validation vs. formatting vs. schema checking

These three operations are related but distinct. Validation (this tool) answers “is this well-formed JSON at all?”. Formatting - see the JSON Formatter - takes valid JSON and rewrites its whitespace for readability or size. Schema checking goes a level deeper and asks whether valid JSON has the right shape: the required fields, correct types, and allowed values defined in a JSON Schema document. A sensible debugging workflow is validate first, format second (so you can read the document), then worry about schema-level correctness.

Practical tips

• Validate configuration files before deploying - a single trailing comma in a config can take a service down.
• When hand-editing JSON, edit the formatted version (via the formatter) - errors are far easier to avoid when structure is visible.
• If you need placeholder IDs while building test payloads, the UUID Generator produces valid unique identifiers in bulk.
• Debugging a string field that should match a pattern (emails, dates, SKUs)? Prototype the pattern in the Regex Tester before wiring it into code.

Frequently asked questions