Bot Detection Grounding Data

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 Grounding Data Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as BotDetectionGroundingData. 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": "BotDetectionGroundingData",
  "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 source covers is enough for it to reach for BotDetectionGroundingData on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every source 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": {
    "vervecontext": {
      "url": "https://api.vervecontext.com/v1/mcp"
    }
  }
}

https://api.vervecontext.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.

Why ground on it

A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value in a shape you can check, which is the difference between an answer you can cite and one you have to hedge.

Point an evaluation at userAgent: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.

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 Grounding Data

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

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