User Agent Parser

How to use

1. 1Paste a User-Agent string into the input box, or click Use my User-Agent to load the one your current browser is sending.
2. 2Try a sample (Chrome on Windows, Safari on iPhone, Firefox on Linux, Edge on macOS, Chrome on Android, iPad, Googlebot, GPTBot) to see how the parser handles a typical real-world UA.
3. 3Read the breakdown panel for browser, engine, OS, device kind, brand, model, and bot identity. Each field has its own copy button.
4. 4Glance at the side panel badges to instantly see whether the UA looks like a real visitor or a bot, and which OS, browser, and engine combination it claims.
5. 5Use Copy breakdown for a plain-text summary, or Copy JSON for a structured object you can paste into a log line, a feature flag, or a test fixture.

About this tool

User Agent Parser takes any HTTP User-Agent string and breaks it into the fields developers, QA engineers, analytics teams, and SEO auditors actually need: browser name with full and major version, rendering engine and version (Blink, Gecko, WebKit, EdgeHTML, Trident, Presto, Goanna), operating system with the marketing name your audience recognizes (Windows 10/11, macOS Sequoia, iOS, iPadOS, Android, Chrome OS, Linux distros, FreeBSD, PlayStation, Xbox), device class (desktop, mobile, tablet, smart-tv, console, bot), and brand plus model when the UA exposes one (Pixel, iPhone, iPad, Galaxy SM-S918B, Surface, Kindle, and so on). The parser also identifies a long list of crawlers and link-preview unfurlers by their canonical name, including Googlebot, Bingbot, Applebot, DuckDuckBot, AhrefsBot, SemrushBot, GPTBot, ChatGPT-User, ClaudeBot, PerplexityBot, CCBot, Bytespider, Amazonbot, Slackbot, Discordbot, Twitterbot, facebookexternalhit, LinkedInBot, TelegramBot, WhatsApp, Lighthouse, Puppeteer, Playwright, Selenium, curl, Wget, and Go-http-client, so you know whether the traffic is a human visitor or an automated client before you make a routing or rate-limit decision. The detector understands the quirks of modern UA strings: it handles Chromium's reduced UA where the minor version reads 0.0.0, the iPad-as-desktop trick on iPadOS 13+, the way Edge and Opera both wear Chrome's clothes for compatibility, the difference between Internet Explorer's MSIE token and Trident-only fingerprints, and the way Safari surfaces a frozen Mobile build identifier on iOS. Output is rendered three ways: a copy-ready text breakdown for tickets and bug reports, a labeled side-by-side anatomy panel with at-a-glance badges (real visitor versus bot, mobile versus desktop, OS, browser, engine), and a structured JSON object you can paste straight into log fixtures, Storybook stories, feature-flag conditions, or analytics fingerprints. Notes call out edge cases that are easy to miss, like Chrome's frozen UA and iPad spoofing the desktop Mac UA, so you do not silently misclassify a real device. Useful when debugging a bug only one browser hits, when reading a server access log line and trying to figure out who or what made the request, when validating analytics segmentation, when auditing bot traffic before applying robots.txt or rate-limit rules, when triaging a CSP or feature-policy report, and when building a User-Agent allow-list or block-list. Everything runs entirely in the browser using a curated regex pipeline, so the User-Agent strings you analyze, including any custom strings you might be testing for fingerprint evasion, never leave your device.

Free to use. Works in your browser. No signup, no login.