JSON Path Finder — Get JSONPath from JSON Object

Paste JSON and click on any value to instantly see its JSONPath expression. Navigate nested structures with a clickable tree and copy the exact path to your clipboard. 100% client-side — your data stays private.

JSON Path Finder

Input (JSON)
Click a value to see its path Ready

How to Use the JSON Path Finder

  1. Paste your JSON in the left panel.
  2. The right panel renders a clickable tree of your data.
  3. Click any value — its JSONPath appears in the bar below.
  4. Copy the path to use in code, documentation, or queries.
  5. Use Load Sample to try a demo with nested data.

Why Use This JSON Path Finder

Working with complex JSON often requires knowing the exact path to a value — whether you're writing JSONPath queries, accessing nested fields in code, or debugging API responses. This tool eliminates guesswork by giving you the precise path with a single click.

Unlike manual traversal, the clickable tree visualizes the entire structure so you can explore nested objects and arrays without losing context. The copied path follows standard JSONPath syntax, compatible with libraries in JavaScript, Python, Java, and more.

Frequently Asked Questions

The tool uses dot notation for object keys (e.g., users[0].name) which is compatible with most JSONPath implementations including JavaScript property access, jq, and Python jsonpath libraries.

The tree view is rendered in your browser, so it works well with typical API responses and config files. Very large files (10MB+) may take a moment to render. For extremely large datasets, consider using a desktop tool.

Yes. Clicking an element inside an array shows the index in the path, e.g., users[0].name or items[2]. Both the index and the value are clearly indicated in the tree.

Use Cases

Debugging API Responses

Quickly locate the path to a specific field in deeply nested API response payloads.

Writing JSONPath Queries

Generate the exact path expression to use with JSONPath libraries in your code.

Documenting Data Structures

Map out field paths for documentation when onboarding new team members.

Data Mapping & Transformation

Identify source paths when building ETL pipelines or data transformation scripts.