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TrueVoice MCP

TrueVoice MCP

TrueVoice MCP

Tools to eliminate AI slop from text

Model Context Protocol server with tools to detect and eliminate AI slop from text. Based on expert annotations from NLP writers and philosophers analyzing AI-generated text patterns.

Deploy to Vercel

What is AI Slop?

Low-quality AI text characterized by:

  • Information Utility: Low content density, irrelevant filler, factual errors

  • Style Quality: Repetitive structures, corporate clichés ("delve into", "leverage")

  • Structure: Excessive verbosity, poor coherence, formulaic patterns

Research foundation: arXiv:2509.19163v1

Related MCP server: AI Content Detector MCP Server

Quick Start

One-Click Install

Visit truevoice-mcp.kushagragolash.dev for one-click install buttons for Cursor, VS Code, Claude Code, and Claude Desktop.

Claude Code

claude mcp add --transport http truevoice https://truevoice-mcp.kushagragolash.dev/api/mcp

Claude Desktop

Open Settings > Connectors > Add custom server, paste:

https://truevoice-mcp.kushagragolash.dev/api/mcp

Any MCP Client

Add to your MCP configuration:

{
  "mcpServers": {
    "truevoice": {
      "url": "https://truevoice-mcp.kushagragolash.dev/api/mcp"
    }
  }
}

Local Development (stdio)

{
  "mcpServers": {
    "truevoice": {
      "command": "node",
      "args": ["/path/to/truevoice-mcp/dist/index.js"]
    }
  }
}

See Development for full local setup.

Available Tools

get_human_writing_rules

Get comprehensive anti-slop writing rules tailored to your context.

Parameters:

  • context (optional): Writing type (e.g., "technical blog", "email", "docs")

Example:

Get writing rules for a technical blog post

check_for_slop

Analyze text for AI slop indicators across three dimensions.

Parameters:

  • text (required): The text to analyze

Example:

Check this for slop: "In today's digital landscape, it's important to
note that we should leverage cutting-edge solutions to deliver a
seamless user experience..."

Returns:

⚠️ AI Slop Analysis

- Overused Phrases: Found AI clichés - landscape, it's important to note,
  leverage, cutting-edge, seamless
- Verbosity: Overly long sentences (avg 28.5 words)
- Word Complexity: Unnecessarily formal - "utilize" → "use"

Recommendation: Revise to be more concise, direct, and natural.

get_slop_examples

Get categorized examples of AI slop patterns to avoid.

Parameters:

  • category (optional): "phrases", "structure", "tone", or "all"

Example:

Show me phrase examples to avoid

What Gets Detected

Slop Phrases

  • "delve into" → "explore"

  • "leverage" → "use"

  • "it's important to note" → just state it

  • "robust", "seamless", "holistic", "paradigm shift"

  • "cutting-edge", "game changer", "synergy"

Structural Issues

  • Repetitive sentence starts (same word 3+ times)

  • Excessive bullet points and lists

  • Overly formal language for casual contexts

  • Long sentences (>25 words average)

  • Low lexical density (<40% unique words)

Research-Based Scoring

Text analyzed across three weighted dimensions:

  • Information Utility (β=0.06) - Content density, relevance

  • Style Quality (β=0.05) - Repetition, coherence, naturalness

  • Structure (β=0.05) - Verbosity, bias, flow

Development

Prerequisites

  • Node.js 18+

  • TypeScript 5.6+

  • npm or pnpm

Local Setup

git clone https://github.com/howdoiusekeyboard/truevoice-mcp
cd truevoice-mcp
npm install
npm run build

Available Scripts

  • npm run build - Compile TypeScript

  • npm run dev - Watch mode for development

  • npm start - Run stdio server locally

  • npx ultracite check - Lint check

  • npx ultracite fix - Auto-fix issues

Testing Locally

Test stdio transport (Claude Desktop):

npm run build
npm start
# Server runs on stdio, test with MCP inspector:
npx @modelcontextprotocol/inspector node dist/index.js

Test HTTP transport (Cursor/Web):

vercel dev
# Visit http://localhost:3000

Architecture

Project Structure

truevoice-mcp/
├── api/                    # Vercel serverless functions
│   ├── mcp.ts             # HTTP MCP endpoint (Streamable HTTP)
│   ├── index.ts           # API info page
│   ├── check.ts           # Slop detection API
│   ├── rules.ts           # Rules API
│   └── examples.ts        # Examples API
├── src/                    # Core MCP server
│   ├── index.ts           # stdio transport (Claude Desktop)
│   └── rules.ts           # Anti-slop taxonomy
├── public/
│   └── index.html         # Homepage/docs
└── dist/                   # Compiled output

Dual Transport Support

stdio Transport (Local/Claude Desktop):

  • Direct process communication

  • Low latency, persistent connection

  • Best for local development

  • Entry: dist/index.js

Streamable HTTP Transport (Vercel/Web):

  • POST-only mode (MCP 2024-11-05 spec)

  • Fully stateless, serverless-optimized

  • No SSE (Vercel 60s timeout limitation)

  • Auto-scaling on demand

  • Endpoint: /api/mcp

Technology Stack

  • Runtime: TypeScript 5.6+ with Node.js ESM modules

  • Validation: Zod schemas for type safety

  • Linting: Ultracite (Biome-powered)

  • MCP SDK: @modelcontextprotocol/sdk v1.19+

  • Deployment: Vercel serverless functions

Deploy Your Own

One-Click Deploy

Deploy with Vercel

Manual Deploy

npm install
vercel deploy --prod

Your MCP endpoint: https://your-project.vercel.app/api/mcp

Environment Variables

None required! Server works out of the box.

Usage Examples

In Claude Desktop

"Check my email draft for AI slop patterns"
"Get writing rules for professional documentation"
"Show me examples of phrases to avoid in blog posts"

As Writing Assistant

"Analyze this paragraph and suggest improvements:
[paste text]"

"Get human writing rules for casual Twitter posts,
then help me write a thread"

API Integration

# Check text for slop
curl -X POST https://truevoice-mcp.kushagragolash.dev/api/check \
  -H "Content-Type: application/json" \
  -d '{"text": "Your text here"}'

# Get writing rules
curl https://truevoice-mcp.kushagragolash.dev/api/rules?context=email

Research Foundation

Based on expert annotations from:

  • NLP researchers and writers

  • Professional philosophers

  • Industry content creators

Key Findings:

  • Relevance (β=0.06) - Most significant slop indicator

  • Content Density (β=0.05) - Substantive vs. filler content

  • Natural Tone (β=0.05) - Conversational vs. robotic voice

  • Human perception correlation: AUROC 0.52-0.55

Full paper: arXiv:2509.19163

Documentation

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

Quick checklist:

  • Run npx ultracite fix before committing

  • Keep changes simple and focused

  • Add examples for new patterns

  • Update docs if needed

License

MIT License - see LICENSE for details


Live Demo: truevoice-mcp.kushagragolash.dev MCP Endpoint: https://truevoice-mcp.kushagragolash.dev/api/mcp

Available Tools

3 tools
check_for_slopCheck for AI SlopA

Analyze text for AI slop indicators across three categories: Information Utility, Style Quality, and Structure. Returns specific patterns to avoid.

Inputs: text (required).

get_human_writing_rulesGet Human Writing RulesA

Get comprehensive rules for writing like a human and avoiding AI slop. Use these rules as system-level instructions for any text generation task.

Inputs: context.

get_slop_examplesGet Slop ExamplesB

Get examples of common AI slop phrases and patterns to avoid, categorized by type.

Inputs: category.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.7/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a distinct purpose: retrieving rules, analyzing text for slop, and providing examples. There is no meaningful overlap between them, and their descriptions clearly separate the reference/instructional functions from the analysis function.

    Naming Consistency4/5

    Tool names follow a clear and predictable lowercase snake_case pattern, mostly using get_ for reference tools and check_for_ for the analysis tool. Minor inconsistency exists between get_ and check_for_ as verb styles, but the naming remains readable and consistent overall.

    Tool Count5/5

    Three tools is a well-scoped count for a focused MCP server centered on human writing rules and AI slop detection. Each tool serves a distinct and necessary role without bloat or redundancy.

    Completeness4/5

    The tool surface covers the core domain well: users can learn the rules, see examples, and check their text for slop. A minor gap is the absence of a rewrite/improvement tool, but this is not a significant failure for the apparent advisory/analysis purpose.

    Maintenance

    ActivityStale
    ResponsivenessOutdated data

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