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Jambozx

OnlineCyberTools MCP (280+ filterable tools)

webdev_user_agent

Read-onlyIdempotent

Parse any User-Agent string to identify browser, engine, OS, device, CPU, and features. Detect bots, crawlers, and headless browsers with detailed flags.

Instructions

User-Agent String Parser. Parse a User-Agent string you supply into structured browser, engine, OS, device, CPU, and feature data, and flag whether it is a bot/crawler/headless agent. It parses the userAgent value in the request body — it does not read the caller's own request header; pair it with network_request_headers to inspect live headers instead. Runs locally on the input: read-only, non-destructive, contacts no external service, and is rate-limited. Returns parsed browser/engine/os/device/cpu/features plus isBot, botType, botPurpose and suspicious/commonCrawler/headlessBrowser flags.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userAgentYesThe User-Agent string to parse, e.g. a browser or bot UA header value. Required; an empty/blank value returns HTTP 400.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNoWhether parsing succeeded.
parsedNoStructured breakdown of the User-Agent string.
isBotNoTrue when the UA matches a known bot/crawler/HTTP-client keyword.
botTypeNoBot category (Search Engine, Social Media, Messaging, Command Line Tool, Programming Language, Unknown Bot) when isBot, else null.
botPurposeNoInferred bot purpose (Web Indexing, Content Preview, Site Monitoring, Data Fetching, Content Access) when isBot, else null.
suspiciousNoTrue for scripted/scraper UAs (python/curl/wget/bot/crawl/scrape) excluding googlebot/bingbot.
commonCrawlerNoTrue for a known search crawler (googlebot, bingbot, slurp, duckduckbot, baiduspider, yandexbot).
headlessBrowserNoTrue when the UA indicates headless/PhantomJS/Selenium automation.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations (readOnly, non-destructive, idempotent), description adds that it runs locally, contacts no external service, is rate-limited, and details output flags like isBot, botType, etc. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

4-5 sentences, each adding unique value. Front-loaded with purpose, then behavior, then output. No superfluous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given single parameter and complex output, description adequately explains both input constraints (empty returns 400) and output structure (browser, OS, bot flags). Output schema exists, so not required to list every field, but description covers categories.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema already covers userAgent with description and examples. Description adds context that it parses the value in the request body, not the caller's header, but this is a clarification on usage rather than parameter semantics. Still, it's helpful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it parses a user-agent string into structured browser/engine/OS/device/CPU/feature data and checks for bots. Distinguishes itself from sibling network_request_headers by noting it does not read the caller's own header.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly explains when to use (when supplying a UA string) and when not to (do not use to read caller's header), and suggests pairing with network_request_headers. Provides clear alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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