JSON Tree Viewer

What Is This Tool?

A JSON tree viewer turns a JSON document into a navigable outline: every object and array becomes a node you can expand or collapse, every key shows its inferred type, and every leaf value is displayed inline. Instead of scrolling through thousands of lines of text, you drill down only into the branches you actually care about.

This is different from a JSON formatter. A formatter rewrites the text of your JSON with indentation so it looks nicer — it's the right tool when you just need to pretty-print, minify, or validate syntax. A tree viewer is for exploring and navigating the structure itself, especially when the JSON is large, deeply nested, or you don't yet know where the data you need is located. If you just want to prettify or validate JSON text, use the JSON Formatter instead.

Why Use It?

• Navigate deeply nested API responses or config files without losing track of which bracket belongs to which level.
• Search by key name or value and jump straight to the match, with the path automatically expanded for you.
• Handles very large JSON (several megabytes) smoothly — child nodes are only built when you expand them, so nothing freezes the tab.
• See the type of every value at a glance — string, number, boolean, null, object or array — with clear labels.
• 100% private: parsing and rendering happen entirely in your browser, nothing is uploaded or stored.

How to Use

1. Paste your JSON into the input box, or use the file picker to load a JSON file from disk.
2. Click "Render tree" to build the interactive view.
3. Click the arrow next to any object or array to expand or collapse it — nodes deeper than a couple of levels start collapsed automatically so large files stay responsive.
4. Type a key name or value into the search box to find matches; the tool expands every parent node on the way down and scrolls to and highlights the result.
5. Use the next/previous buttons to step through multiple matches.

Example

Input

{"user":{"id":42,"name":"Ada","roles":["admin","editor"],"active":true,"manager":null}}

Output

user: { 4 keys }
  id: 42 (number)
  name: "Ada" (string)
  roles: [ 2 items ]
    0: "admin"
    1: "editor"
  active: true (boolean)
  manager: null

Each row shows the key, its inferred type, and either the value (for leaves) or a collapsed count (for objects and arrays) until you expand it.

Practical tips

• For huge API responses, search for a distinctive field name first (like an id or an error code) instead of manually expanding node by node — the search jumps straight there.
• Nodes past the first couple of levels start collapsed on purpose, so a multi-megabyte payload stays responsive; expand only the branch you need.
• Type badges (string, number, boolean, null, object, array) are especially useful for spotting a field that's unexpectedly null or an array where you expected an object.
• If you only need to pretty-print or validate a JSON snippet rather than explore its structure, the JSON Formatter is faster for that job.

Where this fits in real workflows

Deeply nested API responses, database exports, and configuration files are hard to reason about as flat text — you lose track of which closing brace matches which key. Loading the same payload into a tree view lets you collapse everything you don't need and focus only on the branch that matters, which is much faster than scrolling through a formatted wall of text looking for one field.

A common flow: paste a large webhook payload here first to understand its shape and find the field you need, then switch to the JSON Formatter if you need a clean, indented text copy to paste into a bug report or code review.

→ JSON Formatter

Common use cases

• Exploring a large, deeply nested API response to find where a specific field lives before writing code against it.
• Reviewing a big configuration or export file without scrolling through thousands of lines of raw text.
• Checking the shape and types of an unfamiliar JSON payload before parsing it in your own code.
• Locating a specific value (an ID, an error message, a timestamp) buried somewhere inside a large JSON document.

Frequently Asked Questions