User Agent Parser
LiveParse user agent strings to identify browser, OS, and device information.
Understanding Browser User Agents
Every HTTP request includes a User-Agent header — a string that identifies the client application, operating system, device type, and rendering engine. Browsers like Chrome, Firefox, and Safari each construct this string differently, embedding version numbers, platform identifiers, and compatibility tokens. Parsing user-agent strings is essential for analytics, device-specific rendering, bot detection, and debugging browser-specific issues, but the format is notoriously inconsistent and packed with legacy artifacts like "Mozilla/5.0" that appear in virtually every modern browser.
Parse any user agent string to extract detailed information about the browser, OS, device type, and rendering engine.
The Devkitr User Agent Parser breaks down any user-agent string into its component parts: browser name and version, operating system and version, device type (desktop, mobile, tablet), rendering engine, and bot identification. Paste a user-agent string from server logs, HTTP headers, or analytics data to immediately understand what client sent the request.
In a typical development workflow, User Agent Parser becomes valuable whenever you need to parse user agent strings to identify browser, os, and device information. Whether you are working on a personal side project, maintaining production applications for a company, or collaborating with a distributed team across time zones, having a reliable browser-based inspection tool eliminates the need to install desktop software, write one-off scripts, or send data to third-party services that may log or retain your information. Since User Agent Parser processes everything locally on your device, your data stays private and your workflow stays uninterrupted — open a browser tab, paste your input, get your result.
Key Features
Comprehensive Browser Detection
Identifies Chrome, Firefox, Safari, Edge, Opera, Samsung Internet, UCBrowser, and dozens of other browsers including their exact version numbers.
OS and Device Classification
Detects the operating system (Windows, macOS, Linux, Android, iOS) and classifies the device as desktop, mobile, tablet, smart TV, or game console.
Bot and Crawler Identification
Recognizes Googlebot, Bingbot, GPTBot, and other automated crawlers, distinguishing them from real user traffic for analytics accuracy.
Rendering Engine Extraction
Identifies the underlying engine — Blink, Gecko, WebKit, or Trident — which determines actual CSS and JavaScript capabilities regardless of browser brand.
How to Use User Agent Parser
Obtain a User-Agent String
Copy a user-agent string from browser DevTools (navigator.userAgent), server access logs, analytics platforms, or HTTP request headers.
Paste into the Parser
Enter the full user-agent string into the input field. The parser processes the entire string including legacy compatibility tokens.
Read the Breakdown
Review the parsed components: browser, version, OS, device type, engine, and whether the client is a known bot or crawler.
Apply the Insights
Use the parsed information to debug rendering issues, filter analytics data, configure device-specific features, or identify suspicious bot traffic.
Use Cases
Debugging Browser-Specific Bugs
Parse the user-agent from a bug report to identify the exact browser version and rendering engine, narrowing down which CSS or JS behavior to investigate.
Filtering Analytics Bot Traffic
Identify crawler and bot user-agents in your access logs to exclude them from traffic analytics and get accurate human visitor counts.
Implementing Device-Specific Features
Parse user-agents to detect mobile vs desktop clients when server-side rendering needs to deliver different layouts or feature sets.
Investigating Security Incidents
Analyze unusual user-agent strings in access logs during security reviews to identify automated attacks, scrapers, or spoofed clients.
Pro Tips
Never rely solely on user-agent parsing for feature detection — use feature detection (Modernizr, CSS @supports) for capabilities and user-agent only for analytics.
Watch for Chrome's User-Agent reduction initiative — newer Chrome versions send simplified user-agent strings with less specific version and platform information.
Bot user-agents can be easily spoofed — verify legitimate crawlers by reverse DNS lookup on the request IP address, not just the user-agent string.
Test your user-agent parsing logic with edge cases: embedded WebView browsers, Electron apps, and curl clients all send unconventional user-agent strings.
Common Pitfalls
Using user-agent parsing for browser feature detection
Fix: Use feature detection APIs instead. User-agent strings are unreliable for capabilities because browsers spoof each other's tokens for compatibility.
Assuming all "Mozilla/5.0" user-agents are Firefox
Fix: Almost every modern browser includes "Mozilla/5.0" as a legacy compatibility token. Parse the full string to identify the actual browser.
Blocking requests based solely on user-agent strings
Fix: User-agents are trivially spoofable. Combine user-agent analysis with IP reputation, request patterns, and rate limiting for effective bot management.
Frequently Asked Questions
QWhat information can be extracted from a user agent?
Browser name and version, operating system, device type (desktop/mobile/tablet), and rendering engine.
QCan I parse my own browser's user agent?
Yes. The tool automatically detects your current browser's user agent, or you can paste any user agent string manually.
QIs user agent data reliable for detection?
User agent strings can be spoofed, but they are generally accurate for analytics and basic feature detection.
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