JSON Tree Viewer
Visualize JSON data as an interactive collapsible tree. Color-coded by data type. Expand and collapse nodes to explore nested structures. All local.
How to Use JSON Tree Viewer
Paste Your JSON
Paste any valid JSON into the input area — an object, array, or even a single value. The tool will parse it and render a collapsible tree.
Explore the Tree
Click the arrows (▶) to expand collapsed nodes and see nested objects and arrays. The tree shows data types with color coding for quick scanning.
Copy What You Need
Click any value to copy it to your clipboard. The status bar at the bottom shows the total number of keys and the maximum nesting depth.
What the Colors Mean
Frequently Asked Questions
How does the tree view help with debugging?
When you get a large JSON response from an API, scrolling through thousands of lines of formatted text is inefficient. A collapsible tree lets you collapse the parts you don't need and drill into the specific section you're debugging. The type color coding also makes it easy to spot when a value is a string when you expected a number, or vice versa.
Can I view very large JSON files?
Yes, but performance depends on your browser. For JSON under a few megabytes, the tree renders almost instantly. For very large files (10MB+), the browser may pause briefly during parsing. The tree view renders lazily — only the top-level nodes are visible until you expand them, which helps with rendering performance.
What do the colors mean?
Object keys are purple, strings are green, numbers are blue, booleans are orange, and null is gray. Arrays show their length in brackets. This color scheme helps you quickly scan the structure and spot data type inconsistencies.
Why a Tree View Beats Formatted JSON
When you run JSON.stringify(obj, null, 2) and stare at the output, you're looking at a linear representation of a hierarchical structure. For a small object with 10 keys, that's fine. For an API response with 500 lines across 6 levels of nesting, scrolling back and forth trying to match brackets and follow the structure is slow and error-prone.
A collapsible tree matches how the data is actually structured. Collapse the parts you've already checked; expand only the section you're currently investigating. The indentation and connecting lines make the parent-child relationships visually obvious in a way that flat indented text can't.
The type coloring is the other big advantage. In a plain text dump, "false" and false look nearly identical, but one is a string and the other is a boolean — and that distinction matters when your code does strict type checking.