Utilities

User Agent Parser

Parse and analyze browser User-Agent strings

User-Agent String

Presets:

About

User agent parser that extracts browser name/version, rendering engine (Blink, WebKit, Gecko, Trident), operating system (name, version, architecture), device type (mobile, tablet, desktop, TV, console), and bot/crawler detection. Includes 10 preset user agent strings (Chrome, Firefox, Safari, Edge, Googlebot, Bingbot, etc.), side-by-side UA comparison, and one-click copy as JSON.

User agent strings are long, cryptic, and inconsistently formatted. This tool parses them into readable structured data so developers can make device-specific or browser-specific decisions without manually parsing UA strings.

Who should use this tool?

Web developers, analytics engineers, QA testers, and anyone who needs to understand what browser, OS, or device is behind a user agent string for debugging or analytics.

Common use cases

Parse a real user agent from server logs to identify the visitor's browser and OS
Compare two user agent strings side-by-side to find differences in browser version or platform
Detect if a user agent belongs to a known bot or crawler (Googlebot, Bingbot, etc.)
Load preset UAs for Chrome, Firefox, Safari, Edge to test parsing accuracy
Copy the parsed result as JSON for integration into an analytics pipeline
Determine if the device is mobile, tablet, or desktop from the user agent string

How to Use

Paste a user agent string into the input field; the parsed result updates automatically.

Review the parsed fields: Browser (name, version, engine), OS (name, version, architecture), Device (type, vendor, model), and Bot (boolean + name).

Click a preset button (Chrome, Firefox, Safari, Edge, Googlebot, Bingbot, etc.) to load a sample UA string.

Use the Compare button to load the UA string into a side-by-side comparison view with another UA.

Click Copy JSON to copy the entire parsed result as a JSON object to your clipboard.

Check the Bot Detection section to see if the UA is identified as a known crawler with its specific name.

Examples

Input: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" → Browser: Chrome 120, Engine: Blink 120, OS: Windows 10 64-bit, Device: Desktop, Bot: No

Input: "Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)" → Browser: Googlebot 2.1, OS: unknown, Device: unknown, Bot: Yes (Googlebot)

Best Practices

Use parsed OS and device data for analytics segmentation, not for feature detection (use feature detection instead)
Compare multiple UA presets to understand how different browsers format their user agent strings
Use the JSON export to feed parsed UA data into data warehouses or analytics platforms
Check bot detection when filtering traffic — some legitimate UAs may not be in the bot list
Test with real user agents from production logs, not just the presets

Common Mistakes

Using user agent detection for feature availability — use feature detection APIs (e.g., Modernizr) instead
Assuming a mobile user agent always means a mobile screen — tablets also send mobile UAs in some modes
Treating the browser version number as a simple integer — versions can be semantic (e.g., 120.0.6099.109)
Relying solely on user agent for bot detection — some bots disguise their UA as a real browser
Confusing the rendering engine with the browser — Safari uses WebKit, Chrome uses Blink (forked from WebKit)

FAQ

Can it parse iOS user agents? Yes

iOS Safari, Chrome, and other browsers are parsed correctly with OS name "iOS" and device model like "iPhone" or "iPad".

How accurate is bot detection? It detects over 50 known crawlers (Googlebot, Bingbot, DuckDuckBot, Yandex, Baidu, Slurp, etc.) by matching patterns in the UA string.

Does it support custom UA databases? Not yet

the parser uses a built-in rule set updated for modern browsers.

What does "engine" mean? Engine is the browser rendering engine (Blink, WebKit, Gecko, Trident) which determines CSS/HTML feature support independent of the browser vendor.

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Learning Resources

Dive deeper with our comprehensive guides and tutorials.

User Agent Parser - Beginner's Guide

5 min read

User Agent Parser Advanced Techniques

8 min read

About

Who should use this tool?

Web developers, analytics engineers, QA testers, and anyone who needs to understand what browser, OS, or device is behind a user agent string for debugging or analytics.

Common use cases

Parse a real user agent from server logs to identify the visitor's browser and OS
Compare two user agent strings side-by-side to find differences in browser version or platform
Detect if a user agent belongs to a known bot or crawler (Googlebot, Bingbot, etc.)
Load preset UAs for Chrome, Firefox, Safari, Edge to test parsing accuracy
Copy the parsed result as JSON for integration into an analytics pipeline
Determine if the device is mobile, tablet, or desktop from the user agent string

How to Use

Paste a user agent string into the input field; the parsed result updates automatically.

Review the parsed fields: Browser (name, version, engine), OS (name, version, architecture), Device (type, vendor, model), and Bot (boolean + name).

Click a preset button (Chrome, Firefox, Safari, Edge, Googlebot, Bingbot, etc.) to load a sample UA string.

Use the Compare button to load the UA string into a side-by-side comparison view with another UA.

Click Copy JSON to copy the entire parsed result as a JSON object to your clipboard.

Check the Bot Detection section to see if the UA is identified as a known crawler with its specific name.

Examples

Input: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" → Browser: Chrome 120, Engine: Blink 120, OS: Windows 10 64-bit, Device: Desktop, Bot: No

Input: "Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)" → Browser: Googlebot 2.1, OS: unknown, Device: unknown, Bot: Yes (Googlebot)

Best Practices

Use parsed OS and device data for analytics segmentation, not for feature detection (use feature detection instead)

Compare multiple UA presets to understand how different browsers format their user agent strings

Use the JSON export to feed parsed UA data into data warehouses or analytics platforms

Check bot detection when filtering traffic — some legitimate UAs may not be in the bot list

Test with real user agents from production logs, not just the presets

Common Mistakes

Using user agent detection for feature availability — use feature detection APIs (e.g., Modernizr) instead

Assuming a mobile user agent always means a mobile screen — tablets also send mobile UAs in some modes

Treating the browser version number as a simple integer — versions can be semantic (e.g., 120.0.6099.109)

Relying solely on user agent for bot detection — some bots disguise their UA as a real browser

Confusing the rendering engine with the browser — Safari uses WebKit, Chrome uses Blink (forked from WebKit)

FAQ

Can it parse iOS user agents? Yes

iOS Safari, Chrome, and other browsers are parsed correctly with OS name "iOS" and device model like "iPhone" or "iPad".

How accurate is bot detection? It detects over 50 known crawlers (Googlebot, Bingbot, DuckDuckBot, Yandex, Baidu, Slurp, etc.) by matching patterns in the UA string.

Does it support custom UA databases? Not yet

the parser uses a built-in rule set updated for modern browsers.

What does "engine" mean? Engine is the browser rendering engine (Blink, WebKit, Gecko, Trident) which determines CSS/HTML feature support independent of the browser vendor.

User Agent Parser

About

Who should use this tool?

Common use cases

How to Use

Examples

Best Practices

Common Mistakes

FAQ

Related Tools

Same Category — Utilities

Word Counter

Regex Tester

Markdown Preview

IP Address Calculator

Popular Tools

JSON Formatter

Base64 Encoder/Decoder

JWT Decoder

Learning Resources

Share

User Agent Parser

About

Who should use this tool?

Common use cases

How to Use

Examples

Best Practices

Common Mistakes

FAQ

Related Tools

Same Category — Utilities

Word Counter

Regex Tester

Markdown Preview

IP Address Calculator

Popular Tools

JSON Formatter

Base64 Encoder/Decoder

JWT Decoder

Learning Resources

Share