MCP Tooling Setup

papertowel provides a Model Context Protocol (MCP) server that allows AI assistants (like Claude Desktop) to interact directly with your codebase’s AI fingerprints.

The `papertowel-mcp` Server

The MCP server exposes the core functionality of the Scrubber as a set of tools that the AI can call. This allows the AI to “self-diagnose” its own fingerprints and suggest fixes.

Available Tools

Tool	Description
`papertowel_scan`	Scans a directory for AI fingerprints and returns a structured report of findings.
`papertowel_scrub`	Applies fixes to the detected fingerprints in a target directory.
`papertowel_grade`	Grades a file or directory from A+ to F for overall AI fingerprint presence.

Installation

1. Build the Server

First, build the MCP server binary:

cargo build --release -p papertowel-mcp

2. Configure Claude Desktop

Add the server to your claude_desktop_config.json (usually located at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "papertowel": {
      "type": "stdio",
      "command": "papertowel-mcp",
      "args": [],
      "env": {
        "RUST_LOG": "info"
      }
    }
  }
}

Usage in Chat

Once configured, you can simply ask Claude to clean up your code:

“Scan my current directory for AI fingerprints and tell me what you find.”
“Run the papertowel scrubber on the src/ directory to remove any obvious slop.”
“Grade this repo and explain which categories contributed most to the score.”

The AI will call papertowel_scan, papertowel_scrub, and papertowel_grade as needed, receive the results, and report back to you.

Keyboard shortcuts

papertowel