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reviewradar-detect-mcp

v0.1.0

Published

MCP server for AI-powered fake review detection — analyze product reviews for authenticity, detect review manipulation patterns, calculate trust scores, and identify suspicious reviewer behavior across e-commerce platforms

Vulnerabilities

Powered byPowered by Snyk
  • 0High
  • 0Medium
  • 0Low

Links

Git

Maintainers

crawdecrawde

Keywords

mcpmodel-context-protocolfake-reviewsreview-detectiontrust-scoree-commerceproduct-reviewsreview-fraudsentiment-analysisconsumer-protectionamazon-reviewsreview-manipulation

Readme

reviewradar-detect-mcp

AI-powered fake review detection MCP server. Analyze product reviews for authenticity, detect manipulation patterns, score reviewer credibility, and grade product review trustworthiness.

Tools

analyze_reviews

Analyze a batch of product reviews for fake/manipulated content. Evaluates linguistic patterns (superlative abuse, generic phrasing, incentivized language), checks verified purchase status, and returns per-review trust scores (0-100) with risk flags.

detect_patterns

Detect corpus-level manipulation patterns across reviews. Identifies temporal clustering (review burst campaigns), copy-paste text duplication via 4-gram overlap analysis, and rating distribution anomalies (astroturfing, review bombing, bimodal campaigns).

score_reviewer

Evaluate a reviewer profile for suspicious behavior. Checks review velocity, all-5-star patterns, single-brand concentration, account age, verified purchase rate, and review length to produce a credibility score.

grade_product

Calculate an aggregate product authenticity grade (A-F). Evaluates overall review corpus: rating distribution shape, verified purchase %, review velocity trends, category comparison, and incentivized review presence.

Install

npx reviewradar-detect-mcp

Claude Desktop Config

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

License

MIT