To parse a user agent string, paste it into the utilAZ User Agent Parser and the tool instantly breaks it into browser name and version, operating system, device type, and rendering engine. Programmatically, use libraries like ua-parser-js in JavaScript or user-agents in Python. Parsing works by matching known token patterns (e.g., Chrome/120.0, Windows NT 10.0) against a regularly updated database of browser and device signatures.

A user agent parser can extract the browser name and full version number, the rendering engine (Blink, Gecko, WebKit), the operating system name and version, the device type (desktop, mobile, tablet, smart TV, console), the device brand and model on mobile, whether the visitor is a known bot or crawler, and the CPU architecture (x86, ARM). Some advanced parsers also infer the form factor and whether the browser supports specific web standards.

To detect a bot from its user agent, check for known crawler tokens such as Googlebot, Bingbot, Slurp, DuckDuckBot, Baiduspider, YandexBot, facebookexternalhit, and Twitterbot. Also look for generic indicators like 'bot', 'crawl', 'spider', or 'fetch' anywhere in the string. The utilAZ User Agent Parser flags recognized bots automatically. Keep in mind that sophisticated scrapers may use normal-looking user agents, so combine UA checks with behavioral analysis for stronger bot detection.

The traditional User-Agent header sends all device information in a single string on every request, which can be spoofed and contributes to fingerprinting. Client Hints (Sec-CH-UA headers) are a newer replacement where the browser sends only low-entropy data by default and the server must explicitly request high-entropy details like full version or device model. Client Hints improve privacy, reduce parsing complexity, and give servers structured key-value data instead of a monolithic string. Both mechanisms coexist today, but Chrome is progressively reducing the information in the legacy UA string.

To parse multiple user agents at once, paste them line by line into the utilAZ User Agent Parser batch mode and the tool returns a table with browser, OS, device, and bot status for each entry. Programmatically, loop through your list using a parsing library, or use a REST API service that accepts arrays of UA strings. Batch parsing is commonly used to analyze web server access logs, identify traffic sources in analytics exports, and audit device distributions across large datasets.