MCP Content Credentials Server

MCP Content Credentials Server

Enables reading and verifying C2PA Content Credentials from images and videos through both embedded manifests and invisible watermarks. Supports direct filesystem access, URL checking, and provides structured provenance data including creator identity, AI generation info, and content authenticity.

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README

MCP Content Credentials Server

MCP (Model Context Protocol) server for reading C2PA Content Credentials from images and videos. Detects credentials from both embedded manifests and invisible watermarks.

Features

  • šŸ” Embedded C2PA Detection - Read manifests from file metadata
  • 🌊 TrustMark Watermark Detection - Detect credentials in image pixels (survives social media!)
  • 🌐 URL Support - Check credentials from web URLs
  • šŸ“‚ Direct Filesystem Access - Claude can browse your directories
  • ⚔ Smart Detection - Checks embedded first, watermark as fallback
  • šŸ¤– Automatic Installation - Zero configuration setup
  • šŸ“‹ Structured Output - Human-readable parsed data
  • šŸ›”ļø Production Ready - Full error handling and logging
  • 🌐 REST API - HTTP endpoints for ChatGPT and web integration

Quick Start

# 1. Clone
git clone https://github.com/noga7/mcp-content-credentials.git
cd mcp-content-credentials

# 2. Install (automatic: installs c2patool + TrustMark)
npm install

# 3. Build
npm run build

# 4. Configure Claude Desktop
# Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
  "mcpServers": {
    "content-credentials": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-content-credentials/build/index.js"]
    }
  }
}

# 5. Restart Claude Desktop

# Optional: Start REST API for ChatGPT/web access
npm run start:api
# Server runs on http://localhost:3000

REST API (for ChatGPT & Web Apps)

Want to use this with ChatGPT or your own web app? Start the HTTP REST API:

npm run start:api

The server runs on http://localhost:3000. See REST-API.md for full documentation.

For ChatGPT: Use ngrok to expose your local server, or deploy to Render/Railway. See REST-API.md for instructions.

# Quick test
curl "http://localhost:3000/verify-url?url=https://example.com/image.jpg"

Prerequisites

  • Node.js v18+
  • Python 3.8.5+ (for TrustMark watermarks)

All other dependencies auto-install during npm install:

  • āœ… c2patool (Homebrew on macOS, binary on Linux)
  • āœ… TrustMark Python package (via pip)

Manual Installation (if auto-install fails)

# c2patool
brew install contentauth/tools/c2patool  # macOS

# TrustMark
pip3 install trustmark Pillow

# Or retry auto-install
npm run install-deps

Usage

Check a Specific File

"Check content credentials in ~/Desktop/photo.jpg"
"Is this image AI-generated?"
"Who created /Users/you/Downloads/image.png?"

Browse Directories

"What images are in my Desktop?"
"Check my Downloads for Content Credentials"
"Find AI-generated images in my Pictures"

Check URLs

"Check credentials at https://example.com/image.jpg"

How It Works

Detection Flow

1. Check Embedded C2PA Manifest (fast: ~150ms)
   ↓
   Found? → Return immediately āœ…
   ↓
2. Check TrustMark Watermark (slower: ~600ms)
   ↓
   Found? → Return watermark data āœ…
   ↓
3. Neither found → "No Content Credentials found" āŒ

Why This Order?

  • Performance: 80% of credentialed images have embedded manifests
  • Speed: Skip expensive watermark check when not needed
  • Completeness: Still catch stripped metadata via watermarks

TrustMark Watermarks

Invisible watermarks embedded in image pixels that:

  • āœ… Survive JPEG compression
  • āœ… Persist through social media uploads (Instagram, Twitter)
  • āœ… Work after print-scan cycles
  • āœ… Remain when metadata is stripped

Supported Formats

Images: JPEG, PNG, WebP, GIF, TIFF, AVIF, HEIC
Video: MP4, MOV

API Response

{
  success: boolean;
  hasCredentials: boolean;
  
  // Embedded C2PA data
  manifestData?: {
    whoThisComesFrom?: {
      linkedInIdentity?: { name, profileUrl, verified }
      otherIdentities?: [{ name, socialAccounts }]
    };
    aboutThisContent?: {
      actions?: [{ action, softwareAgent, when }]
      genAIInfo?: { generative, training, model }
    };
    aboutTheseCredentials?: { claimSigner, timestamp };
    validationInfo?: { certificate, trustInfo };
  };
  
  // Watermark data (if no embedded found)
  trustMarkData?: {
    identifier: string;    // Watermark payload
    schema: string;        // BCH_SUPER, BCH_5, etc.
    manifestUrl?: string;  // URL to full manifest
  };
  
  error?: string;
}

Filesystem Access

Claude can browse these directories automatically:

  • ~/Desktop
  • ~/Downloads
  • ~/Documents
  • ~/Pictures

No need to provide exact paths! Just ask:

  • "What images are in my Desktop?"
  • "Check recent downloads"

Development

npm run build        # Compile TypeScript
npm run dev          # Development mode
npm run lint         # Check code quality
npm run test         # Run tests
npm run precommit    # Full quality check

Architecture

mcp-content-credentials/
ā”œā”€ā”€ src/
│   ā”œā”€ā”€ index.ts              # MCP server + filesystem access
│   ā”œā”€ā”€ c2pa-service.ts       # Detection orchestration
│   ā”œā”€ā”€ trustmark-service.ts  # Watermark detection (Python)
│   ā”œā”€ā”€ parsers/              # Data formatters
│   └── types/                # TypeScript definitions
ā”œā”€ā”€ scripts/
│   ā”œā”€ā”€ install-trustmark.cjs # Auto-installer
│   └── trustmark-decode.py   # Python watermark decoder
└── build/                    # Compiled output

Troubleshooting

"Unable to access that file"

  1. Restart Claude Desktop (most common fix!)
  2. Use absolute paths: /Users/you/... not ~/...
  3. Verify MCP is connected: Ask "What tools do you have?"

"c2patool: command not found"

brew install contentauth/tools/c2patool  # macOS
# or
npm run install-deps

"Python or TrustMark not found"

pip3 install trustmark Pillow
# or
npm run install-deps

No Content Credentials Found

This is normal! The file either:

  • Wasn't created with content authentication
  • Had credentials removed
  • Is a screenshot/copy without provenance

Performance

  • Embedded check: ~150ms (fast path, 80% of cases)
  • + Watermark check: ~600ms (fallback, 20% of cases)
  • First watermark: ~30s (downloads ONNX model, one-time)

Security

  • āœ… Read-only filesystem access
  • āœ… Limited to user directories (Desktop, Downloads, etc.)
  • āœ… Input validation on all paths and URLs
  • āœ… Temporary files auto-deleted
  • āœ… No access to hidden/system files

Contributing

See CONTRIBUTING.md

Resources

License

MIT

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