AIMentionTracker

ai.aimentiontrackerPublished by aimentiontracker.aiOfficial publisherv0.1.3Updated Oct 24, 2026

How often ChatGPT, Claude, Gemini and Perplexity name and cite your brand, with the evidence.

VerifiedStreamable HTTPWeb executableData & AnalyticsBusiness & Commerce

Overview

AI-generated overview

AIMentionTracker is a read-only MCP server that shows how often AI assistants like ChatGPT, Claude, Gemini and Perplexity name and cite your brand.

What you can do
Check identity, plan and reporting thresholds, and get today's date and trailing windows before reasoning about dates (get_me, get_current_date). List the brands and questions a workspace tracks, with answer counts per question. Read AI visibility per engine and brand, share of voice, and sentiment counts over a window. See which competitors are named instead of you, the stored answers with mentions and citations, and the domains engines read. Review alerts and ranked recommendations, plus Search Console data where that integration is enabled.
When to use it
Use it when you want to measure or explain your brand's presence in AI-generated answers (answer engine optimisation) and compare it with competitors, or when you need evidence from the actual answers and sources behind those numbers.
Requirements
Either the hosted remote endpoint, authenticated with an OAuth bearer token, or the local npm package run with npx, which needs Node.js and the AMT_API_KEY environment variable. An API key is created in the AIMentionTracker app; keys are scoped to one organisation.
Before you install
The API key is a secret passed in the Authorization header or AMT_API_KEY; keep it private. Access is read-only and cannot change billing, the team or what is tracked, and the server itself holds no secrets. Numbers can be null when there are too few answers, and engines are reported separately rather than averaged.

Installation

In SourceWeft

  1. Open AIMentionTracker in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.aimentiontracker%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "aimentiontracker": {
      "type": "http",
      "url": "https://mcp.aimentiontracker.ai/mcp"
    }
  }
}

README

@aimentiontracker/mcp

Track how often ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews name and cite your brand, from inside your MCP client. Twelve read-only tools over AI visibility, share of voice, sentiment, competitor mentions and what to do about them, with the answers they came from.

This is answer engine optimisation (AEO) data, not rank tracking: the unit is an answer an assistant gave a real question, and whether you were in it.

Hosted (no install)

bash
claude mcp add --transport http aimentiontracker https://mcp.aimentiontracker.ai \  --header "Authorization: Bearer amt_live_YOUR_KEY"

Local (stdio)

bash
claude mcp add aimentiontracker -e AMT_API_KEY=amt_live_... -- npx -y @aimentiontracker/mcp

Create a key at app.aimentiontracker.ai/api-keys. Keys are read-only and scoped to one organisation; they cannot change billing, the team, or what is tracked.

Tools

All read-only. v1 has no write endpoints, deliberately: adding a prompt expands a metered bill and triggering a run spends real vendor money.

ToolWhat it answers
get_meWho this key is, the plan, and the reporting thresholds. Call first.
get_current_dateToday in UTC, and the trailing windows every other tool counts back from. Call before reasoning about dates.
list_brandsWhich brands this key can read, and their ids
list_questionsThe questions this workspace runs, and how many answers each produced. Call before reading a disappointing number: it may be the wrong question, not poor visibility
get_visibilityPresence per engine and per brand over a window
get_share_of_voiceEach tracked brand's mentions as a share of the tracked set
get_sentimentRecommended, negative and neutral counts per brand, against the classified denominator
list_competitorsWho gets named instead of you, including answers that named them and never mentioned you
list_answersThe stored answers, with mentions and citations
list_sourcesDomains the engines read before answering
list_alertsFindings worth acting on
list_recommendationsWhat to do next, ranked, with the pages and answers behind each item. Check displayable: false means the corpus is too thin to rank, not that there is nothing to do

One further tool, list_search_console, registers only where the Google Search Console integration is enabled. A tool that always answers 404 is worse than an absent one: an agent picks it for a task it cannot do and spends a turn failing.

Three rules the tools enforce

  1. A null rate means "not enough answers yet", never zero. Rendering it as 0% reports a collapse that did not happen.
  2. Engines are never averaged. They disagree; a mean describes no real surface.
  3. An empty findings list does not mean nothing changed. list_alerts says so in the payload, not just the description.

Every tool that reports a measurement carries these rules in its own description, because an agent reads the tool, not the README.

Why the denominators are in the payload

get_share_of_voice returns brands_counted, and get_sentiment counts against classified rather than total mentions. A workspace tracking two competitors and one tracking twelve produce incomparable shares from identical answers, and the sentiment classifier abstains on listicle mentions where an engine named a brand without endorsing it. Both numbers are meaningless without the denominator beside them, so the tools return it rather than trusting the caller to ask.

Security

The hosted server holds no secrets. No database, no vendor credentials, no service account. Your key arrives in the Authorization header and is passed straight through to the API, which does all authentication, tenancy, entitlement and rate limiting. Each request gets a fresh, stateless server instance that is closed when the response ends.

More

MIT.

Source: README.md at commit 5d14262

Tools

0
This server asks you to sign in, so SourceWeft could not read its tools without an account and has not indexed them. What a connected account sees can depend on that account and its permissions.

Version history

2
  1. v0.1.3LatestOct 9, 2026
  2. v0.1.2Oct 1, 2026

Score

85% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts