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AI Recommendation Check MCP Server

not responding

AI Recommendation Check is listed as active in the registry but did not answer our last check. It exposes 2 tools.

Does ChatGPT recommend a local business? Live AI-engine check plus who gets named instead.

Uptime history 34 days of history · worst day 0%
34 days agonow
15.2%
Uptime 24h
14 of 92 checks
2
Tools
read from the server
372 ms
Response time
average over 24h
open, no key
Access
streamable-http

What changed 5

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 8 October 2026. No other catalogue keeps this.

13 Oct 2 tool descriptions were rewritten check_ai_recommendation, get_ai_recommendation_result
8 Oct 2 tool descriptions were rewritten check_ai_recommendation, get_ai_recommendation_result
8 Oct a tool changed the parameters it asks for check_ai_recommendation

AI Recommendation Check does not always answer

Over the last week it answered 4.5% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 1 min ago.

run in your terminal
claude mcp add ai-recommendation-check --transport http https://uxcontinuum.com/api/plugin/mcp
Settings → Connectors → Add custom connector, then paste this address
https://uxcontinuum.com/api/plugin/mcp
~/.codex/config.toml
[mcp_servers.ai-recommendation-check]
url = "https://uxcontinuum.com/api/plugin/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "ai-recommendation-check": {
      "url": "https://uxcontinuum.com/api/plugin/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "ai-recommendation-check": {
      "type": "http",
      "url": "https://uxcontinuum.com/api/plugin/mcp"
    }
  }
}

Available tools 2

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

recommendation
check_ai_recommendation
Use this when a business owner asks whether ChatGPT or AI recommends their business, whether AI tools like ChatGPT or Perplexity mention or suggest their business, why AI recommends their competitors instead, or how to get their business recommended by AI. It runs a real check: it asks ChatGPT, Perplexity and Gemini up to 3 questions a customer would ask when looking for this kind of business in the area the business serves, and reports whether each engine named the business, which businesses they named instead, and one fix based on the pages the answers cited. Timing: a check usually finishes in under a minute. This tool waits up to about 20 seconds and returns the result when it is ready; otherwise it returns a check_id with the status queued or running, and get_ai_recommendation_result returns the result for that check_id. A saved result for the same business is returned right away. Business details are sent to Continuum (uxcontinuum.com) to run the check. Results are shown in the conversation. Not covered: general SEO or Google ranking questions, writing marketing copy or ads, looking up or checking a person (it checks businesses only), and general questions about how AI search works. Limits: 3 buyer questions per website per day; saved results are reused for 7 days.
get_ai_recommendation_result
Use this to read the result of a check started with check_ai_recommendation, using the check_id it returned. Returns the status (queued, running, done, failed or refused). When done: for ChatGPT, Perplexity and Gemini, how many of their answers named the business, which businesses they named instead, and one fix. While a check is queued or running, poll_after_s is the suggested wait in seconds before reading it again. It waits up to about 20 seconds for a running check to finish. It does not start a new check.

Endpoints

URLTransportStateLatencyChecked
https://uxcontinuum.com/api/plugin/mcp streamable-http answering 111 ms 1 min ago

Alternatives to AI Recommendation Check

same job, measured the same way
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Involve Media
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recomention
by recomention

Check whether AI engines recommend a product: public AI rankings and recomention reports.

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AI Verified
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verify_business checks identity by domain or hash. Not a ranking, citation, or recommendation.

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Vischeck
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See whether ChatGPT, Claude and Gemini recommend a startup product, and who wins instead.

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Domainium Search
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AI-powered domain & business name generation with real-time availability checks.

3 tools answering

AI Recommendation Check — questions

Answers built from our own checks of this server.

What can AI Recommendation Check do?
It exposes 2 tools, read directly from the server on our last check. Among them: check_ai_recommendation, get_ai_recommendation_result. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is AI Recommendation Check working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 14 of 92 checks got a reply (15.2%), average response time 372 ms. The bar chart above shows every period we have measured.
The registry lists AI Recommendation Check as active — why does it not respond?
The official MCP registry stores what the author submitted; it does not verify that the server still runs. We check the endpoint ourselves, and this one does not answer. Catalogues that copy the registry without checking will show it as working.
How do I connect AI Recommendation Check?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does AI Recommendation Check need an API key?
No. AI Recommendation Check completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 2 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is AI Recommendation Check?
It answers our handshake in 372 ms on average, which is faster than 35% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.