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ai-visibility-tracker

AI Visibility Tracker: is your brand mentioned and cited in AI search? — $0.05 per answer checked ($0.04 on Gold) + $0.50 per optional report. Runs on Apify; API, Python, JavaScript and MCP examples.

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Use tool

Set up

Hosted by its author. Add the URL to your agent — nothing to install.

~/Library/Application Support/Claude/claude_desktop_config.json
Settings → Connectors → Add custom connector

Name: ai-visibility-tracker
URL:  https://mcp.apify.com/?tools=automationnation/ai-visibility-tracker

same format Cursor, GitHub Copilot CLI, Junie, JetBrains AI Assistant, Augment (Auggie CLI), Factory Droid, Kiro, Devin CLI +12

Values in angle brackets are placeholders. Restart Claude Desktop after editing its config.Claude Desktop docs

README

synced Oct 14, 2026

AI Visibility Tracker: is your brand mentioned and cited in AI search?

Run on Apify

AI Visibility Tracker is an Apify Actor that shows whether AI search engines mention and cite your brand. For each prompt it asks Google AI Overviews, Gemini and Claude the way a customer would. It records whether your brand is named, its position against competitors, how it's described, which sites are cited, every other brand named and what changed since the last run, at $0.05 per answer plus $0.50 for an optional client-ready report.

Price: $0.05 per answer checked ($0.04 on Gold) + $0.50 per optional report · Run it: https://apify.com/automationnation/ai-visibility-tracker · Guide: https://retracn.github.io/automationnation-actors/ai-visibility-tracker/

Quick facts

  • Engines: Google AI Overviews (late-loading overviews read in a real browser), Gemini with Google Search grounding, and Claude with web search, localised to your country.
  • Per answer: whether your brand is named and its position among tracked brands, whether your site is cited and at what position, competitors named or cited, sentiment with a one-line summary, every brand named, and the cited URLs.
  • Hidden competitors: every company or product named in the answers is counted, including ones you don't track.
  • Weekly tracking: each run is compared with the last, with mentions and citations gained or lost per prompt and engine, a client-ready HTML report with a trend over time, and Slack, Discord or webhook alerts.
  • Price: $0.05 per answer checked ($0.045 Silver, $0.04 Gold and above) plus $0.50 per optional report; answers that couldn't be checked are free. 20 prompts on 3 engines weekly costs about $14 a month.

Example input

{
  "brand": "Notion",
  "domain": "notion.so",
  "competitors": [
    "Obsidian (obsidian.md)",
    "Evernote (evernote.com)"
  ],
  "prompts": [
    "What is the best note-taking app for teams?"
  ],
  "engines": [
    "google-ai-overviews",
    "gemini",
    "claude"
  ]
}

Run it from code

REST API

curl -X POST "https://api.apify.com/v2/acts/automationnation~ai-visibility-tracker/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"brand": "Notion", "domain": "notion.so", "competitors": ["Obsidian (obsidian.md)", "Evernote (evernote.com)"], "prompts": ["What is the best note-taking app for teams?"], "engines": ["google-ai-overviews", "gemini", "claude"]}'

Python — see examples/python_example.py

# pip install apify-client
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("automationnation/ai-visibility-tracker").call(run_input={
  "brand": "Notion",
  "domain": "notion.so",
  "competitors": [
    "Obsidian (obsidian.md)",
    "Evernote (evernote.com)"
  ],
  "prompts": [
    "What is the best note-taking app for teams?"
  ],
  "engines": [
    "google-ai-overviews",
    "gemini",
    "claude"
  ]
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("engineLabel"), item.get("visibility"), item.get("brandRank"), item.get("prompt"))

JavaScript — see examples/node_example.mjs

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('automationnation/ai-visibility-tracker').call({
  "brand": "Notion",
  "domain": "notion.so",
  "competitors": [
    "Obsidian (obsidian.md)",
    "Evernote (evernote.com)"
  ],
  "prompts": [
    "What is the best note-taking app for teams?"
  ],
  "engines": [
    "google-ai-overviews",
    "gemini",
    "claude"
  ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const item of items) console.log(item.engineLabel, item.visibility, item.brandRank, item.prompt);

Use it with AI agents (MCP)

Hosted MCP server URL (Claude, ChatGPT, Cursor and other clients with remote MCP support):

https://mcp.apify.com?tools=automationnation/ai-visibility-tracker

Local config for Claude Desktop / Cursor — mcp/claude_desktop_config.json:

{
  "mcpServers": {
    "ai-visibility-tracker": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/actors-mcp-server",
        "--tools",
        "automationnation/ai-visibility-tracker"
      ],
      "env": {
        "APIFY_TOKEN": "YOUR_APIFY_TOKEN"
      }
    }
  }
}

FAQ

What is AI visibility tracking? Checking whether AI assistants and AI search features name and cite your brand when people ask about your market, and how that changes over time. It's the measurement side of generative engine optimization (GEO).

Which AI engines does it check? Google AI Overviews, Gemini (with Google Search grounding) and Claude (with web search). ChatGPT and Perplexity are planned.

How much does it cost? $0.05 per answer checked ($0.04 on Gold and above), plus $0.50 per run for the optional report. One answer is one prompt on one engine; answers that couldn't be checked are free.

Can it find competitors I don't know about? Yes. Every company or product the answers name is listed, tracked or not, so the brands AI engines recommend instead of you show up in the report.

More from AutomationNation

This repository holds usage examples. The scraper itself runs on the Apify platform; you need a free Apify account and API token. Examples are MIT licensed.

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