JSON Formatter
Format, minify, search, and navigate JSON with collapsible sections, path inspection, and syntax highlighting.
How it works
Three steps from raw JSON to the exact data you need.
Paste your JSON
Drop in any JSON payload -- API responses, config files, database exports, or clipboard data. No size limit on what you can paste.
Format and explore
Instantly get syntax-highlighted, indented JSON with a collapsible tree. Click any node to expand, collapse, or inspect its path.
Copy what you need
Copy the formatted output, the minified version, a type schema for LLM context, or any node path -- all with a single click.
Why use this formatter
Built for developers who work with JSON daily. Not just pretty-printing -- actual tools for exploring and understanding data structure.
Collapsible tree view
Navigate large JSON structures by expanding only the sections you care about. Collapse entire arrays or objects with one click to focus on the data that matters.
Search across keys and values
Find any key or value instantly with Ctrl+F. Results are highlighted in place with match navigation, and collapsed sections auto-expand to reveal hidden matches.
Type schema for LLM context
Auto-generate a TypeScript-style type schema from your JSON. Copy it directly into LLM prompts to describe data structure without sending the full payload.
Path inspector with one-click copy
Click any line to see its full access path as a breadcrumb. Copy the dotted path notation with one click -- ready to paste into your code or jq queries.
Common use cases
Whether you are debugging a REST API or building an LLM prompt, this formatter gets you from raw data to understanding faster.
Paste API responses to inspect nested data, verify structure, and find specific values. The collapsible tree makes it easy to drill into deeply nested response payloads.
Used by backend engineers, QA teams, and frontend developers integrating third-party APIs.
Validate and format JSON configuration files before deploying. Catch syntax errors early, verify key-value pairs, and see the full structure at a glance with stats and depth indicators.
Used by DevOps engineers, system admins, and platform teams managing infrastructure-as-code.
Extract type schemas from JSON to describe data structures in LLM prompts without sending the entire payload. Save tokens while giving the model the context it needs to understand your data format.
Used by AI engineers, prompt designers, and anyone building LLM-powered applications with structured data.