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reviewradar-response-mcp

v0.1.0

Published

MCP server for review response generation — craft professional responses to positive and negative reviews, analyze sentiment, generate response templates, and manage review reputation

Vulnerabilities

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  • 0Medium
  • 0Low

Links

Maintainers

crawdecrawde

Keywords

mcpmodel-context-protocolreviewradarreview-responsereputation-managementreview-replycustomer-feedbackgoogle-reviewsyelp-reviewstrustpilotreview-sentimentbusiness-reputationcustomer-servicereview-management

Readme

reviewradar-response-mcp

Review response generation MCP server — craft professional responses to customer reviews, analyze sentiment patterns, generate response templates, and manage online reputation.

Tools

| Tool | Description | |------|-------------| | generate_review_response | Generate personalized, professional responses to 1-5 star reviews with recovery strategies | | analyze_review_sentiment | Analyze a batch of reviews for sentiment patterns, complaint themes, and reputation health | | generate_response_templates | Generate reusable response templates by rating level and complaint category | | review_reputation_score | Calculate reputation health score from review distribution, response rate, and trends | | competitive_review_analysis | Compare your review profile against competitors for strengths and vulnerabilities |

Installation

npx reviewradar-response-mcp

Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "reviewradar-response": {
      "command": "npx",
      "args": ["-y", "reviewradar-response-mcp"]
    }
  }
}

Environment Variables (Optional)

REVIEWRADAR_API_URL=https://fakescan.site
REVIEWRADAR_API_KEY=your-api-key

Examples

Generate Response to Negative Review

Use generate_review_response with:
- reviewText: "Terrible experience. Waited 45 minutes for food that was cold. Staff was rude when I complained."
- rating: 1
- businessName: "Mario's Italian Kitchen"
- businessType: "restaurant"
- includeOffer: true

Analyze Batch of Reviews

Use analyze_review_sentiment with an array of reviews containing text and rating

License

MIT — fakescan.site