Track your brand’s AI visibility. Save the ranking checks once. Build a daily or weekly history.

Turn the rankings primitive into a repeatable tracker for the queries and brands that matter. Cite42 stores every scheduled result so you can review mention rate, average position, and the per-model breakdown in the dashboard or through MCP.

  • Daily or weekly
  • Stored run history
  • No subscription
  • MCP accessible
Create trackerInstall MCP

Step 1: Create your account

Get $1 in test credit to try your first calls.

Create free account

Step 2: Connect Cite42 MCP

Replace cite42_live_... with your key, then run this once.

Step 3: Ask inClaude Code

You ask your AIDo AI answers mention Cite42 for AI visibility tracking, and where do we rank against Profound and Peec AI?
MCP runs/v1/rankings
Runs across the sources shown.
Your AI saysCite42 appears in 3 of 5 AI sources. It is strongest for API or MCP prompts; Profound leads enterprise-monitoring prompts...
TRACKER REPORT QUESTIONS

Ask your AI about stored tracker data.

After a scheduled or manual run, Cite42 stores the structured result and comparable change so your connected AI can retrieve and summarize it through MCP.

  • How often does AI recommend my brand?

    You ask your AI“How often does AI recommend my brand?”
    MCP runs/v1/rankings
    Your AI saysYour brand has a 0.71 mentionRate and 2.3 avgPosition in the latest run. Claude gives it the strongest position. It includes the key result, source context, and next step...

  • Which model ranks me best, which worst?

    You ask your AI“Which model ranks me best, which worst?”
    MCP runs/v1/rankings
    Your AI saysChatGPT most often places the brand first. Gemini returns no position on two saved checks in the latest run. It includes the key result, source context, and next step...
AI VISIBILITY HISTORY

Track the same brand rankings over time.

Save the buyer questions and brand terms that matter, run the rankings primitive daily or weekly, and keep each comparable result available in the dashboard and through MCP.

  • Store mention rate, average position, and per-model results.
  • Keep prompt wording and model coverage consistent between runs.
  • Review the latest result, history, and comparable deltas.
WHAT WE QUERY

Sources Cite42 checks.

Cite42 queries AI answers, search demand, and conversation signals, then returns normalized results your app or agent can use.

  • ChatGPT

    OpenAI · Search when needed

  • Claude

    Anthropic · Search when needed

  • Perplexity

    Perplexity Sonar · Web-grounded

  • Gemini

    Google · Google Search grounding

  • Google AI Overviews

    Google Search · Live SERP

  • Google data

    Google data

    Search demand signal

  • Reddit

    Conversation signal

  • YouTube

    Video demand signal

HOW IT WORKS

Save. Schedule. Review.

Save up to 25 checks, choose daily or weekly, then review every stored report in Cite42 or through MCP.

  1. Choose the queries and brand names to measure.
    Each saved check uses one buyer query and a list of brands or domains. Add several checks to cover the category questions that matter to your market.
  2. Run the saved checks daily or weekly.
    Choose the AI surfaces, local run time, and timezone. Confirm a per-run cost ceiling before activation so the tracker pauses if the current estimate rises above it.
  3. Review every run in Cite42 or through MCP.
    Compare stored mentionRate, avgPosition, and byModel results over time, or ask your AI agent to retrieve the same tracker history.
EXAMPLE USE CASES

Three ways to use this tracker.

A few practical ways teams use AI visibility tracker.

  • Visibility baseline

    Save repeatable ranking checks.

    Store one buyer question and the brand or domain terms you want ranked in each check, with the same selected AI models each time.
  • Recurring runs

    Run daily or weekly.

    Confirm the maximum credits per run, activate the schedule, and pause it whenever you no longer want recurring billed checks.
  • Agent access

    Ask your AI for the history.

    Use MCP to list trackers, inspect their configuration, and retrieve stored run reports without copying data out of the dashboard.
PRICING

Runs use normal per-call pricing.

Creating, managing, and reading a tracker is free. Scheduled and manual runs bill the saved /v1/rankings checks at the listed per-model rate, up to the cost ceiling you confirm when activating.

Underlying primitivePriceWhat you get
POST/v1/rankings$0.01-$0.07/modelMention rate, average position, and by-model rank, $0.01-$0.07/model depending on surface, all five for $0.22
See all primitive prices and source coverage
KEEP EXPLORING

All endpoints

Same API key, same credit balance, different question.

QUESTIONS

Questions about AI visibility tracker.

It stores the result of each scheduled /v1/rankings check: mentionRate, avgPosition, and byModel for every tracked brand, together with the tracker run history.
A tracker accepts 1 to 25 saved checks. Each rankings check contains one query, at least one brand or domain, and an optional model selection.
Yes. Choose a daily or weekly cadence, an IANA timezone, and a local run time. Weekly trackers also use a selected weekday.
Yes. The tracker MCP tools can list trackers and retrieve stored reports, so an authorized AI agent can work with the same data shown in Cite42.
Every saved check uses the normal /v1/rankings price for its selected models. Tracker management and stored history do not add a subscription fee.
You confirm a maximum cost per run when activating the tracker. A new estimate at or below that ceiling can run at the current price; an estimate above the ceiling pauses the tracker for review.
READY WHEN YOU ARE

Create your first AI visibility tracker.

Save ranking checks, choose a daily or weekly cadence, and keep mentionRate, avgPosition, and byModel history available in Cite42 and through MCP.

Create trackerInstall MCP