Find AI Mode queries in your Search Console data

Google counts an AI Mode follow-up question as a new query, so AI conversations leave fragments in your Performance report. genai_conversation_queries finds them and sorts them into seven buckets.

Why AI conversations show up as queries

Google reports traffic from AI Overviews and AI Mode in the Performance report, inside the Web search type, alongside ordinary results (Google Search Central). And when someone asks a follow-up question in AI Mode, Google treats it as a new query, crediting the impressions, position and clicks of the follow-up to that query (Search Console Help). Both checked on 13 October 2026.

The result is that conversation fragments sit in your query list next to ordinary searches, with real impressions, positions and clicks. Search Console does not label them. genai_conversation_queries finds them by their shape and sorts them by what produced them.

The seven buckets

Bucket	What it is	Typical shape
`artefact`	A person replied to Google's AI mid-conversation, and the reply was logged as a query your page appeared for. Positions here are AI-block positions, not open-web rankings.	yes, go on, tell me more
`pivot`	A mid-conversation comparison. It names the alternative people ask the AI about next.	what about X, how about X
`conversational`	A question shaped by conversation with an AI rather than by a search box.	can you…, how do I…, is it worth…, questions of ten or more words
`tracker_probe`	Synthetic prompts from AI-visibility tracking tools passing through Google's grounding layer. Machine traffic, not demand.	… my location is X., evaluate the X on Y
`agent_harness`	Complete agent instructions logged verbatim as a query. Machine traffic.	search the web for…, do not invent…
`pasted_string`	Error messages and CSV header rows entered as searches, by people or pipelines.	comma-separated header rows, Search Console status messages
`long_uncategorised`	Ten or more words with no other marker: quoted sentences, agent fragments, rare long-tail. Review by hand.	long queries matching none of the above

Reading the result

Leave tracker_probe and agent_harness out of any demand analysis. They are machine-generated views. If you run an AI-visibility tracker, the probes may be its own; if you do not, someone else is tracking topics you rank for.
pivot rows name the alternatives people ask about next, which makes them a ready list for a comparison section on the page they land on.
Conversational queries with impressions and almost no clicks can mean the page is being read inside answers rather than clicked from results.
The monthly timeline shows when reply artefacts first appeared for your site.

What it cannot see

Google excludes anonymised (rare) queries, so every number is a floor, not a total.
AI Overviews and AI Mode cannot be told apart at query level; both fold into the web search type.
Classification reads the shape of a query, not intent. A phrase that looks conversational can be typed deliberately, so treat single rows as evidence rather than statistics.
Search Console data does not identify who runs a tracker or an agent.

A real answer

Asked: “Do any of k-o.pro's queries look like AI conversations?”
genai_conversation_queries on the hosted instance, 13 October 2026; empty buckets, the long-tail bucket and the monthly timeline left out

{
  "_meta": {
    "source": "Google Search Console API (live data)",
    "tool": "genai_conversation_queries",
    "parameters": {
      "days": 480,
      "min_impressions": 1,
      "max_rows_per_bucket": 10,
      "include_timeline": true,
      "site_url": "sc-domain:k-o.pro"
    },
    "note": "All numbers in this response come directly from the Google Search Console API. They are exact values, not estimates. Base your analysis only on this data. Do not invent or assume additional context."
  },
  "data": {
    "period": {
      "startDate": "2025-06-20",
      "endDate": "2026-10-12"
    },
    "total_conversation_queries": 4,
    "total_conversation_impressions": 20,
    "buckets": {
      "conversational": {
        "total_matched": 2,
        "rows": [
          {
            "query": "how can i implement bulk tracking across chatgpt, perplexity, and gemini for 15+ accounts?",
            "impressions": 9,
            "clicks": 0,
            "ctr": 0,
            "position": 89.6,
            "top_pages": [
              {
                "page": "https://k-o.pro/posts/track-traffic-from-ai-chatbots-ga4",
                "impressions": 9
              }
            ]
          },
          {
            "query": "is it hard to make a chrome extension",
            "impressions": 1,
            "clicks": 0,
            "ctr": 0,
            "position": 51,
            "top_pages": [
              {
                "page": "https://k-o.pro/posts/how-to-build-a-chrome-extension",
                "impressions": 1
              }
            ]
          }
        ]
      }
    }
  }
}

Four queries in 16 months, all low volume: two conversational questions, each landing on the post that answers it. No reply artefacts like "yes" or "go on" on this site, which the timeline confirms month by month.

Parameters

Every tool that reads a property also takes site_url, so one connection covers every property your Google account can see. Ask for list_properties to get the exact strings: sc-domain:example.com and https://example.com/ are different properties with different data.

Parameter	Default	Note
`days`	480	the full 16 months Search Console keeps
`min_impressions`	1
`max_rows_per_bucket`	50
`include_timeline`	true

The query detection comes from Suganthan's GSC MCP, the project this server is forked from.

Your account

The same group holds the controls over what this server keeps about you.

set_default_property

Saves a default property for your account, so tool calls that do not name one use it.

Ask: “Make sc-domain:example.com my default property.”

Parameter	Default	Note
`site_url`	required	exactly as list_properties reports it

export_my_data

Your identity, the status of your Google connection, your saved settings and how many active tokens exist. It never includes the stored Google credential.

Ask: “Show me everything this server stores about me.”

No parameters.

disconnect_account

Erases the stored Google connection, every token and your saved settings, and ends your open sessions.

Ask: “Disconnect my account and erase what you store.”