Bot Detection Skill

Overview

A bot detection API for crawlers and scrapers. Bot Detector uses a comprehensive database of known bot and crawler user agent patterns to identify automated traffic, categorizing detected bots into types like search engines, social media crawlers, SEO tools, and monitoring services. It also applies list-free heuristics to flag automated clients the database misses — missing user agents and non-browser clients such as curl and scripts — and returns a composite risk score.

Live Test Bot Detection Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as BotDetectionSkill. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

{
  "name": "BotDetectionSkill",
  "arguments": {
    "ua": "Googlebot/2.1 (+http://www.google.com/bot.html)"
  }
}

You do not name the tool yourself; the model picks it. Asking about Googlebot/2.1 (+http://www.google.com/bot.html) in the terms this skill covers is enough for it to reach for BotDetectionSkill on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every skill in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervekit": {
      "url": "https://api.vervekit.com/v1/mcp"
    }
  }
}

https://api.vervekit.com/v1/mcp

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

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{
  "status": "ok",
  "error": null,
  "data": {
    "userAgent": "Googlebot/2.1 (+http://www.google.com/bot.html)",
    "isBot": true,
    "bot": {
      "name": "Googlebot",
      "category": "search_engine",
      "url": "http://www.google.com/bot.html",
      "reputation": "trusted",
      "shouldBlock": false
    },
    "isAutomated": true,
    "verified": true,
    "riskScore": 0,
    "riskLevel": "low"
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

A call costs 10 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Analytics Filtering

Exclude bot traffic from your analytics to get accurate visitor metrics and user behavior data

Access Control

Implement different behavior for bots vs real users, such as rate limiting or content restrictions

Security Monitoring

Identify potentially malicious crawlers and scrapers attempting to access your content

SEO Insights

Track which search engine bots are crawling your site and how frequently

Other ways to use Bot Detection Skill

Set up Bot Detection Skill on VerveKit, or reach the same source a different way. Your VerveKit account and credits work on all of them — one key, one balance.

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