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Tools
track_ai_answer_visibility
Check whether AI answers name and cite a brand for the questions its buyers ask. Give brand_name, brand_domain, and questions (for example "best crm for small business"). Each question is asked samples times (default 3) on each engine: google_ai_overview needs no key; openai (ChatGPT), anthropic (Claude), perplexity, and gemini run on the caller's own API keys, which this server reads from its env
brand_name string · required
The brand to look for in the answers, as people write it, for example HubSpot. Matched as a whole word, any case.
questions array · required
1 to 50 questions buyers ask, written the way they would type them, for example best crm for small business.
brand_domain string
The brand website domain, such as hubspot.com. An answer that cites a page on it, or on a subdomain, counts as cited.
engines array
Where to ask. Default google_ai_overview only. openai, anthropic, perplexity, and gemini need that vendor's API key in this server's environment; the model use is billed to the key owner by the vendor
samples string
How many times each question is asked on each engine, 1 to 10. Default 3.
competitors array
Up to 20 competitors to track in the same answers, as a name, a domain, or name|domain (Pipedrive|pipedrive.com).
brand_aliases array
Other ways answers write the brand, such as a product name. Up to 10.
country string
Two letter country code for Google, such as us or gb. Default us.
language string
Language code for Google, such as en or de. Default en.
include_answer_text string
true (default) returns the answer text up to 8,000 characters on each sample row; false returns the 300 character excerpt only.
openai_model string
Model for the openai engine. Default gpt-5-mini.
anthropic_model string
Model for the anthropic engine. Default claude-sonnet-5-5.
perplexity_model string
Model for the perplexity engine. Default sonar.
gemini_model string
Model for the gemini engine. Default gemini-2.5-flash.
max_charge_usd string
Optional. The run stops before it would charge more than this.
A call is made on an account: it counts against an allowance and the publisher sees it, which is why this one asks who you are first.
96/100
trust score
1
tool declared
remote
via our gateway
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p95 latency
What it does
Ask the questions your buyers ask, then see which AI engines name your brand and which cite your pages. It returns sample rows, named and cited rates per question, competitor rates, and cited sources.
Quickstart
# 1 — sign in once: npx mcprush@latest login
# it asks for a key from mcprush.com/dashboard#access
# 2 — install
npx mcprush@latest add mambalabs/ai-answer-visibility-tracker-mcp
# 3 — ask your agent for something these tools do
# track_ai_answer_visibility
Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither.
AI Answer Visibility Tracker costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publisher
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine — this server runs on infrastructure we host behind our gateway, and what you install is the connection to it.
Claude Codenot declared — it may still work
Claude Code has its own MCP command, and the key rides on it as a header — the gateway refuses a call that carries none. Claude Code reads MCPRUSH_KEY each time it connects, so the key stays out of its config: export your key from Access in your shell profile (macOS, Linux), or run setx MCPRUSH_KEY <your key> and open a new terminal (Windows). Or let npx mcprush@latest add mambalabs/ai-answer-visibility-tracker-mcp write the entry with the key for you; --scope user makes it available in every project. The first connection after a quiet spell starts the server, which takes up to a minute: if your client says it failed to connect, reconnect after that (/mcp in Claude Code).
claude mcp add --transport http --scope user ai-answer-visibility-tracker-mcp https://mcprush.com/gw/ai-answer-visibility-tracker-mcp/mcp --header 'Authorization: Bearer ${MCPRUSH_KEY}'Reconnect, or start a new session, and the tools appear in the model’s tool list.
Free to install on mcprush: no card. The gateway still answers a key, so you sign in once — which is also what gives you saved lists, release alerts and a budget cap.
What it asks of you
It reaches a system of yours, so it needs your own credential rather than the publisher’s: APIFY_TOKEN — Your Apify API token. Runs are billed to your own Apify account.. You set it after installing; the value is sealed here and handed to the server when it starts.
What it writes
One config entry pointing at the gateway. The server itself runs on infrastructure we host, so nothing from this listing executes on your machine.
What you approve
1 tool, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Check whether AI answers name and cite a brand for the questions its buyers ask. Give brand_name, brand_domain, and questions (for example "best crm for small business"). Each question is asked samples times (default 3) on each engine: google_ai_overview needs no key; openai (ChatGPT), anthropic (Claude), perplexity, and gemini run on the caller's own API keys, which this server reads from its env
| Parameter | Type | Required | Notes |
|---|---|---|---|
| brand_name | string | yes | The brand to look for in the answers, as people write it, for example HubSpot. Matched as a whole word, any case. |
| questions | array | yes | 1 to 50 questions buyers ask, written the way they would type them, for example best crm for small business. |
| brand_domain | string | no | The brand website domain, such as hubspot.com. An answer that cites a page on it, or on a subdomain, counts as cited. |
| engines | array | no | Where to ask. Default google_ai_overview only. openai, anthropic, perplexity, and gemini need that vendor's API key in this server's environment; the model use is billed to the key owner by the vendor |
| samples | string | no | How many times each question is asked on each engine, 1 to 10. Default 3. |
| competitors | array | no | Up to 20 competitors to track in the same answers, as a name, a domain, or name|domain (Pipedrive|pipedrive.com). |
| brand_aliases | array | no | Other ways answers write the brand, such as a product name. Up to 10. |
| country | string | no | Two letter country code for Google, such as us or gb. Default us. |
| language | string | no | Language code for Google, such as en or de. Default en. |
| include_answer_text | string | no | true (default) returns the answer text up to 8,000 characters on each sample row; false returns the 300 character excerpt only. |
| openai_model | string | no | Model for the openai engine. Default gpt-5-mini. |
| anthropic_model | string | no | Model for the anthropic engine. Default claude-sonnet-5-5. |
| perplexity_model | string | no | Model for the perplexity engine. Default sonar. |
| gemini_model | string | no | Model for the gemini engine. Default gemini-2.5-flash. |
| max_charge_usd | string | no | Optional. The run stops before it would charge more than this. |
Free
$0 forever
- Every tool, no call limit, and mcprush charges nothing
- A buyer key from your dashboard — the gateway refuses a call without one
- Answers through our gateway, so every call is in your log
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install AI Answer Visibility Tracker or to call it, and its free tier carries no monthly call limit.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
ATrust score 96 / 100
Scanned: 1.0.0 · 29 Oct 2026
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
Threat score100
Client score96
Findings1 threat · 1 capability
Capabilitymoderate
Coveragesource
Verificationrepo
Surface digest7732d30f02f9014fb604008f8856fe0e128b74e29c3b5d60cc0de8fd884c3fd3
Score vectorthreat 100 → client 96
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | moderate | capability blast radius (moderate) — client exposure if the model is manipulated | −3 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (1 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. moderate is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| track_ai_answer_visibility | untrusted-inputexternal-sink | untrusted-input: declares openWorldHint: true (interacts with entities outside the server); external-sink: handler sends an HTTP POST (fetch(https://api.apify.com/v2/acts/${actorPath}/runs?timeout=${ACTOR_RUN_TIMEOUT_SECS}) at build/index.js:80 |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
flow-1
Untrusted input can drive an external action even though no sensitive source is exposed.
Supply chain and provenance
Integrityfirst-seen
Surface digest7732d30f02f9014f
Scanned2026-10-29
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
The gateway serves every install the publisher’s current release, so a release cannot be pinned or rolled back to here yet. The history below is for reading; the current release on file is 0.1.0.
0.1.0
29 Oct 2026
latest- The version this listing went live with, after review.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish AI Answer Visibility Tracker can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.