Review Platform Reputation Enricher MCP server

Review Platform Reputation Enricher MCP Server

An MCP server that resolves a company domain to its Trustpilot rating, review count and claimed status. It wraps the Mamba Labs Trustpilot Reputation Enricher actor on Apify and returns a Clay-ready flat JSON row to any MCP client.

What's Inside

• What it does
• Quick start
• Prerequisites
• Example prompts
• Inputs
• Output
• Example output
• Features
• Full actor documentation
• Mamba Labs GTM Suite
• License

What it does

Give it a company domain and it resolves that company's Trustpilot business unit and returns the TrustScore, review count, star score, the one to five star breakdown, claimed and verified status and categories, through Trustpilot's documented Business Units API. One flat row per company.

This route needs your own Trustpilot API key. Without one every row reports skipped rather than pretending to have looked. The tool keeps four kinds of empty apart: a refused request reports blocked, a domain with no business unit reports notfound, a value nobody could read reports notextractable, and a source that was never queried reports skipped. G2, Capterra and Glassdoor ship as explicit skipped status columns, so the row shape does not change when a source is added.

All of the lookup runs on Apify. This package is a thin client that calls the actor and hands back the result unchanged.

Quick start

You need Node.js 18 or newer and an Apify account with an API token.

Add this to your Claude Desktop config:

{
  "mcpServers": {
    "mamba-review-platform-reputation-enricher": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-review-platform-reputation-enricher"],
      "env": {
        "APIFY_TOKEN": "your-apify-token"
      }
    }
  }
}

Get your token at https://console.apify.com/account/integrations, paste it in, and restart Claude Desktop. The gettrustpilotreputation tool will be available.

You also need your own Trustpilot API key, free to create at developers.trustpilot.com. It is passed as a tool argument rather than an environment variable, so the model supplies it per call.

Prerequisites

Shortened. The full README is on GitHub.