What it does

Hit counts and percentages by traffic_class for the period. Sorted by hits descending. Classes with zero hits are omitted (a missing class means no hits in that period, treat as zero). The 8 classes (Phase 2 Cloudflare-compatible taxonomy): - user: real human visitor with their own browser - ai_user_action: live AI browse — a human is chatting with ChatGPT/Claude/Perplexity/Copilot and the assistant fetched the page on their behalf. Counts as human attention, just AI-mediated. - ai_search: AI search-engine indexers (PerplexityBot, OAI-SearchBot) — your page is a candidate answer in their index - ai_training: AI training crawlers (GPTBot, ClaudeBot, CCBot, Bytespider) — your content lands in training data, no human is actively reading right now - search_index: classic search engines (Googlebot, Bingbot, Yandex, DuckDuckBot) - social_unfurl: link-preview / social-card bots (Slackbot, facebookexternalhit, Twitterbot, LinkedInBot) - scanner: security/uptime/perf monitoring (Censys, Pingdom, Lighthouse, headless Chrome from a cloud range) - bot_other: recognized as a bot but not in any specific bucket, OR a UA we caught spoofing (e.g. a fake "GPTBot" coming from a random EC2 IP) For "how much human traffic did I get?" sum hits where traffic_class is 'user' or 'ai_user_action'. The same union is also exposed as the 'humans' alias in top_user_agents' traffic_class filter. Note on consistency: get_overview's `bot_share` field uses the same human/non-human split (excludes user + ai_user_action), so the two tools agree on what counts as bot traffic. Note on history: rows from before Phase 2 deployed were reclassified by User-Agent only (we don't store IPs for privacy), so older data may under-report scanner-via-cloud-IP and over-attribute spoofed UAs.

Example prompts

This is the AI-crawler-and-bot-aware metric. Ask:

"How much of mysite.com's traffic is bots vs humans vs AI?"
"Show me the traffic class breakdown for the last 30 days."
"How much of the spike yesterday was real users?"

A typical response:

Traffic class breakdown for mysite.com (last 30 days):

  user                  62,148 hits   71.4%   real humans, direct
  ai_user_action         8,402 hits    9.7%   Claude/ChatGPT fetching for a user
  verified_search_bot    6,221 hits    7.2%   Googlebot, Bingbot etc. (FCrDNS-verified)
  ai_crawler             5,847 hits    6.7%   GPTBot, ClaudeBot, PerplexityBot etc.
  unverified_bot         2,841 hits    3.3%   claims search-bot UA, IP fails verify
  cloud_egress             947 hits    1.1%   from cloud IPs (AWS, GCP, Hetzner)
  headless_browser         412 hits    0.5%   chromium-headless, playwright
  unknown                  186 hits    0.2%   couldn't classify

The eight classes are Cloudflare-compatible (their AI Crawl Control taxonomy), so cross-tool comparisons work. Returns a list of { traffic_class, hits, percentage }.

Why this matters:

  • user plus ai_user_action = your real human audience. Sum is what most other analytics tools call "pageviews": they fold both buckets together. We keep them separate because AI-mediated browsing has different attribution characteristics.
  • ai_crawler tells you how aggressively AI training and answer systems are indexing your content. If GPTBot/ClaudeBot/PerplexityBot are a meaningful share, your content is in their training pipelines and answer surfaces. Relevant to AI-search visibility planning.
  • verified_search_bot plus unverified_bot split shows you which "Googlebot" hits are actually Google. We do FCrDNS verification (reverse-DNS plus forward-DNS) plus IP-CIDR matching for known search bot ranges. Mis-claimed Googlebot is a real, common spoofing pattern.
  • cloud_egress plus headless_browser are usually scraping or monitoring tools. Worth knowing if either is unexpectedly high.

For digging into specific bot UAs, follow up with top_user_agents filtered by a class.

Arguments

Name Type Required Description / Default
site_id string required Site identifier from list_sites (8-character base32, e.g. 'wjxayhdd').
period string optional Time window. Keywords: today, yesterday, last_7_days, last_30_days, last_90_days, last_12_months. Or a custom date range YYYY-MM-DD..YYYY-MM-DD (inclusive).
default: last_7_days

How to call it directly

If you're integrating from your own code rather than a chat client, this is the JSON-RPC payload:

curl -X POST https://mcp-analytics.com/mcp \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "traffic_class_breakdown",
    "arguments": {
      "site_id": "abc12345"
    }
  }
}'

Token comes from /settings after you sign up. Replace any required arguments above.

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