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name: glin-profanity-mcp description: 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.

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

Tool	Description
check_profanity	Check text for profanity with detailed results
censor_text	Censor profanity with configurable replacement
batch_check	Check multiple texts at once (up to 100)
validate_content	Get safety score (0-100) with action recommendation

Analysis

Tool	Description
analyze_context	Context-aware analysis (medical, gaming, etc.)
detect_obfuscation	Detect leetspeak and Unicode tricks
explain_match	Explain why text was flagged
compare_strictness	Compare detection across strictness levels

Utilities

Tool	Description
suggest_alternatives	Suggest clean replacements
analyze_corpus	Analyze up to 500 texts for stats
create_regex_pattern	Generate regex for custom detection
get_supported_languages	List all 24 supported languages

User Tracking

Tool	Description
track_user_message	Track messages for repeat offenders
get_user_profile	Get user's moderation history
get_high_risk_users	List 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

• npm: https://www.npmjs.com/package/glin-profanity-mcp
• GitHub: https://github.com/GLINCKER/glin-profanity/tree/release/packages/mcp
• Core library: https://www.npmjs.com/package/glin-profanity