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WizerAPI Review Intelligence MCP Server

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WizerAPI Review Intelligence is listed as active in the registry but did not answer our last check. It exposes 5 tools.

Analyze customer reviews: sentiment, emotion, topics, themes, digests, and drafted replies.

The linked repository no longer exists on GitHub — it was deleted or made private.

Uptime history 91 days of history · worst day 0%
91 days agonow
0.0%
Uptime 24h
0 of 91 checks
5
Tools
read from the server
599 ms
Response time
average over 24h
open, no key
Access
streamable-http

WizerAPI Review Intelligence does not always answer

Over the last week it answered 0.0% 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 14 min ago.

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

Available tools 5

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

analyze
analyze_review
Analyze ONE customer review and get structured JSON: sentiment (score -1..1, label, confidence), dominant emotion, topics, detected language, and optionally a suggested reply (set options.suggest_reply, pick options.reply_tone: professional | friendly | apologetic | concise). Input: review text up to 10,000 chars, optional 0-5 rating and source. METERED: costs 1 AU + 1 AU per 4,000 input chars (a 300-char review ≈ 1.08 AU); byte-identical repeat input is served from cache for 0 AU. Every result reports its au_cost. For many reviews, prefer extract_themes/summarize_reviews over looping this tool one review at a time.
draft
draft_reply
Draft a customer-facing reply to ONE review in a chosen tone (professional | friendly | apologetic | concise, default professional). Input: review text up to 10,000 chars, optional 0-5 rating for context. Returns the reply text and tone. METERED: costs 1 AU + 1 AU per 4,000 input chars (~1 AU for a short review). Every result reports its au_cost. If you also need sentiment/topics for the same review, call analyze_review with options.suggest_reply instead of calling both tools.
extract
extract_themes
Cluster a SET of reviews into recurring themes, each with a label, frequency, theme sentiment, and example quotes. Input: 1-1,000 review strings, each up to 2,000 chars; optional max_themes (1-50, default 8). Use this ONE call instead of looping analyze_review when you need patterns across many reviews. METERED: costs 4 AU + 1 AU per 1,250 total input chars (100 reviews × 300 chars ≈ 28 AU) — check_usage first for large sets. Every result reports its au_cost.
summarize
summarize_reviews
Produce an executive digest of a review SET: headline, highlights, lowlights, and recommended actions. Input: 1-1,000 review strings, each up to 2,000 chars; optional audience (default "product_team") to slant the writeup. Use for leadership-ready takeaways; use extract_themes when you need per-theme frequencies instead. METERED: costs 6 AU + 1 AU per 1,250 total input chars (50 reviews × 300 chars ≈ 18 AU) — check_usage first for large sets. Every result reports its au_cost.
usage
check_usage
Check the current billing period usage for YOUR WizerAPI organization: plan, included AU, used AU, remaining AU, overage so far, and the per-minute rate limit. Costs 0 AU and is never blocked by the session budget. Call this BEFORE large metered jobs (theme extraction over many reviews, long contracts) to confirm quota headroom, and AFTER quota errors to see where you stand.

Endpoints

URLTransportStateLatencyChecked
https://mcp.wizerapi.com/reviews streamable-http answering 599 ms 14 min ago

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WizerAPI Review Intelligence — questions

Answers built from our own checks of this server.

What can WizerAPI Review Intelligence do?
It exposes 5 tools, read directly from the server on our last check. Among them: analyze_review, check_usage, draft_reply, extract_themes, summarize_reviews. 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 WizerAPI Review Intelligence working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 0 of 91 checks got a reply (0.0%), average response time 599 ms. The bar chart above shows every period we have measured.
Is WizerAPI Review Intelligence still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
The registry lists WizerAPI Review Intelligence 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 WizerAPI Review Intelligence?
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 WizerAPI Review Intelligence need an API key?
No. WizerAPI Review Intelligence completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 5 of them are readable on this page. This is what we observed, not what the docs claim.