glin-profanity-mcp

Part of - MCP server for AI assistants

MCP (Model Context Protocol) server for glin-profanity - enables AI assistants like Claude Desktop, Cursor, Windsurf, and other MCP-compatible tools to use profanity detection and content moderation as native tools.

What is MCP?

The Model Context Protocol (MCP) is an open standard developed by Anthropic that allows AI assistants to securely access external tools and data sources. This package turns glin-profanity into an MCP server that AI assistants can use for content moderation.

Features

• 19 Powerful Tools for comprehensive content moderation

• 4 Workflow Prompts for guided AI interactions

• 5 Reference Resources for configuration and best practices

• 24 Language Support - Arabic, Chinese, English, French, German, Spanish, and more

• Context-Aware Analysis - Domain-specific whitelists reduce false positives

• Obfuscation Detection - Catches leetspeak (f4ck) and Unicode tricks

• Batch Processing - Check multiple texts efficiently

• Content Scoring - Get safety scores for moderation decisions

Installation

For Claude Desktop

Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

For Cursor

Add to your Cursor MCP settings (.cursor/mcp.json in your project or global config):

For Windsurf / Other MCP Clients

Local Installation

Available Tools (12)

Core Detection Tools

1. check_profanity

Check text for profanity with detailed results.

Parameters:

• text (required): Text to check

• languages: Array of languages (default: all)

• detectLeetspeak: Detect f4ck, sh1t patterns

• normalizeUnicode: Detect Unicode tricks

• customWords: Additional words to flag

• ignoreWords: Words to whitelist

2. censor_text

Censor profanity by replacing with asterisks or custom characters.

Parameters:

• text (required): Text to censor

• replaceWith: Replacement character (default: *)

• preserveFirstLetter: Keep first letter (f*** instead of ****)

3. analyze_context

Context-aware analysis with domain-specific whitelists.

Parameters:

• text (required): Text to analyze

• domain: medical, gaming, technical, educational, general

• contextWindow: Words to consider around matches (1-10)

• confidenceThreshold: Minimum confidence to flag (0-1)

4. batch_check

Check multiple texts in one operation (up to 100).

Parameters:

• texts (required): Array of texts (max 100)

• returnOnlyFlagged: Only return texts with profanity

5. validate_content

Comprehensive content validation with safety scoring (0-100).

Parameters:

• text (required): Content to validate

• strictness: low, medium, high

• context: Description of content type

Returns: Safety score, action recommendation (approve, review, edit, reject)

6. detect_obfuscation

Detect text obfuscation techniques.

Detects: Leetspeak, Unicode homoglyphs, zero-width characters, spaced characters

7. get_supported_languages

Get list of all 24 supported languages.

Advanced Analysis Tools

8. explain_match

Explain why a word was flagged with detailed reasoning.

Returns:

• Detection method (direct, leetspeak, Unicode)

• Detailed reasoning

• Suggestions for handling

9. suggest_alternatives

Suggest clean alternatives for profane content.

Parameters:

• text (required): Text with profanity

• tone: formal, casual, humorous, professional

10. analyze_corpus

Analyze a collection of texts for profanity statistics (up to 500 texts).

Returns:

• Profanity rate statistics

• Top profane words frequency

• Severity distribution

• Recommendations

11. compare_strictness

Compare detection results across different strictness levels.

Returns: Detection results at minimal, low, medium, high, and paranoid levels with recommendation.

12. create_regex_pattern

Generate regex patterns for custom profanity detection.

Parameters:

• word (required): Base word

• includeVariants: basic, moderate, aggressive

Returns: Ready-to-use regex patterns for JavaScript and Python.

Available Prompts (4)

MCP Prompts provide guided workflows for common tasks.

1. content_moderation

Step-by-step content moderation workflow.

2. content_cleanup

Clean up content containing profanity for safe publishing.

3. audit_report

Generate a comprehensive moderation audit report.

4. filter_tuning

Tune profanity filter settings for your specific use case.

Available Resources (5)

Resources provide reference data accessible to AI assistants.

Example Prompts for AI Assistants

Basic Usage

Advanced Analysis

Batch Operations

Context-Aware

Workflow Automation

Use Cases

Development

Running Locally

Testing with MCP Inspector

Supported Languages

License

MIT - See LICENSE for details.

Links

• Main glin-profanity repo

• MCP Documentation

• Report Issues