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TypeScript
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Get actual User-Agent

get_actual_user_agent

Get a current Windows User-Agent string to avoid CAPTCHA token rejection. Use the same UA across browser context and CapMonster tasks to ensure matching fingerprints.

Instructions

Fetch a current, real-world (Windows) User-Agent string from CapMonster's UA service.

Use ONE User-Agent as a single fingerprint thread across the whole solve — they must all match or the solved token is likely to be rejected:

  1. set it as the patchright browser context's UA (browser-launch flag / device emulation), so the page is loaded with it;

  2. pass the SAME string as the userAgent field of any CapMonster task that accepts one (reCAPTCHA, Turnstile/Cloudflare, FunCaptcha, AWS WAF, DataDome, Imperva, Yidun, TenDI, …);

  3. when the solution comes back with its own userAgent (or headers["User-Agent"]), the token is bound to THAT value — reuse it for the injection and any follow-up requests instead of your original.

CapMonster requires a current Windows-OS UA; a stale/invalid one fails with ERROR_WRONG_USERAGENT, so re-fetch here rather than reusing an old one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.11

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses important behavioral traits: the UA must be current Windows-OS, stale values cause ERROR_WRONG_USERAGENT, and the solution may return its own UA that should be reused. This is substantial context beyond a simple getter.

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?

The description is front-loaded with the core purpose and then uses a numbered list to explain the fingerprint-consistency workflow. Every sentence adds useful guidance without redundancy.

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?

For a parameterless utility, the description is complete: it covers what the tool returns, why freshness matters, how to apply the value, and how to handle the UA returned in the solution. No output schema exists, but the description sufficiently explains the expected value and usage.

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?

The tool has zero parameters, so the baseline is 4. The description adds meaning by explaining how the returned value should be used, although parameter-level detail is irrelevant here.

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?

Description clearly states the tool fetches a current, real-world Windows User-Agent string from CapMonster's service. This is a specific verb+resource and is clearly distinct from the sibling tools like get_balance or create_task.

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

Usage Guidelines4/5

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

Provides explicit guidance on when to use the tool: before starting a solve, and to re-fetch rather than reuse stale UAs. It gives concrete context for using the value consistently across the solve, though it does not explicitly rule out alternative tools or mention cases where it should not be used.

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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