glin-profanity-mcp

MCP server providing profanity detection tools for AI assistants. Use when reviewing batches of user content, auditing comments for moderation reports, analyzing text for profanity before publishing, or when AI needs content moderation capabilities during workflows.

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Install skill "glin-profanity-mcp" with this command: npx skills add thegdsks/glin-profanity-mcp

Glin Profanity MCP Server

MCP (Model Context Protocol) server that provides profanity detection as tools for AI assistants like Claude Desktop, Cursor, and Windsurf.

Best for: AI-assisted content review workflows, batch moderation, audit reports, and content validation before publishing.

Installation

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "glin-profanity": {
      "command": "npx",
      "args": ["-y", "glin-profanity-mcp"]
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "glin-profanity": {
      "command": "npx",
      "args": ["-y", "glin-profanity-mcp"]
    }
  }
}

Available Tools

Core Detection

ToolDescription
check_profanityCheck text for profanity with detailed results
censor_textCensor profanity with configurable replacement
batch_checkCheck multiple texts at once (up to 100)
validate_contentGet safety score (0-100) with action recommendation

Analysis

ToolDescription
analyze_contextContext-aware analysis (medical, gaming, etc.)
detect_obfuscationDetect leetspeak and Unicode tricks
explain_matchExplain why text was flagged
compare_strictnessCompare detection across strictness levels

Utilities

ToolDescription
suggest_alternativesSuggest clean replacements
analyze_corpusAnalyze up to 500 texts for stats
create_regex_patternGenerate regex for custom detection
get_supported_languagesList all 24 supported languages

User Tracking

ToolDescription
track_user_messageTrack messages for repeat offenders
get_user_profileGet user's moderation history
get_high_risk_usersList users with high violation rates

Example Prompts

Content Review

"Check these 50 user comments and tell me which ones need moderation"
"Validate this blog post before publishing - use high strictness"
"Analyze this medical article with medical domain context"

Batch Operations

"Batch check all messages in this array and return only flagged ones"
"Generate a moderation audit report for these comments"

Understanding Flags

"Explain why 'f4ck' was detected as profanity"
"Compare strictness levels for this gaming chat message"

Content Cleanup

"Suggest professional alternatives for this flagged text"
"Censor the profanity but preserve first letters"

When to Use

Use MCP server when:

  • AI assists with content review workflows
  • Batch checking user submissions
  • Generating moderation reports
  • Content validation before publishing
  • Human-in-the-loop moderation

Use core library instead when:

  • Automated real-time filtering (hooks/middleware)
  • Every message needs checking without AI involvement
  • Performance-critical applications (< 1ms response)

Resources

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