MCP Content Credentials Server
# 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
- š **Embedded C2PA Detection** - Read manifests from file metadata
- š **TrustMark Watermark Detection** - Detect credentials in image pixels (survives social media!)
- š **URL Support** - Check credentials from web URLs
- š **Direct Filesystem Access** - Claude can browse your directories
- ā” **Smart Detection** - Checks embedded first, watermark as fallback
- š¤ **Automatic Installation** - Zero configuration setup
- š **Structured Output** - Human-readable parsed data
- š”ļø **Production Ready** - Full error handling and logging
- š **REST API** - HTTP endpoints for ChatGPT and web integration
## Quick Start
```bash
# 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:
```bash
npm run start:api
```
The server runs on `http://localhost:3000`. See [REST-API.md](REST-API.md) for full documentation.
**For ChatGPT:** Use ngrok to expose your local server, or deploy to Render/Railway. See [REST-API.md](REST-API.md) for instructions.
```bash
# 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`:**
- ā
c2patool (Homebrew on macOS, binary on Linux)
- ā
TrustMark Python package (via pip)
### Manual Installation (if auto-install fails)
```bash
# 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)
ā
Found? ā Return immediately ā
ā
2. Check TrustMark Watermark (slower: ~600ms)
ā
Found? ā Return watermark data ā
ā
3. Neither found ā "No Content Credentials found" ā
```
### 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:
- ā
Survive JPEG compression
- ā
Persist through social media uploads (Instagram, Twitter)
- ā
Work after print-scan cycles
- ā
Remain when metadata is stripped
## Supported Formats
**Images:** JPEG, PNG, WebP, GIF, TIFF, AVIF, HEIC
**Video:** MP4, MOV
## API Response
```typescript
{
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
```bash
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/
āāā src/
ā āāā index.ts # MCP server + filesystem access
ā āāā c2pa-service.ts # Detection orchestration
ā āāā trustmark-service.ts # Watermark detection (Python)
ā āāā parsers/ # Data formatters
ā āāā types/ # TypeScript definitions
āāā scripts/
ā āāā install-trustmark.cjs # Auto-installer
ā āāā trustmark-decode.py # Python watermark decoder
āāā 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"
```bash
brew install contentauth/tools/c2patool # macOS
# or
npm run install-deps
```
### "Python or TrustMark not found"
```bash
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
- ā
Read-only filesystem access
- ā
Limited to user directories (Desktop, Downloads, etc.)
- ā
Input validation on all paths and URLs
- ā
Temporary files auto-deleted
- ā
No access to hidden/system files
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md)
## Resources
- [C2PA Specification](https://c2pa.org/specifications/)
- [c2patool](https://github.com/contentauth/c2pa-rs)
- [TrustMark](https://opensource.contentauthenticity.org/docs/trustmark/)
- [MCP Protocol](https://modelcontextprotocol.io)
## License
MIT
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes based on input source: read_credentials_file handles local files while read_credentials_url handles URLs. Their descriptions explicitly specify when to use each tool, eliminating any potential confusion about which to select for a given scenario.
Both tools follow an identical verb_noun pattern (read_credentials_file and read_credentials_url) with perfect consistency. The naming clearly indicates the action (read) and distinguishes the input type (file vs URL) in a predictable manner.
With only 2 tools, the server feels somewhat thin for a Content Credentials domain that could benefit from additional operations like validation, manifest listing, or credential creation. While the two tools cover the core reading functionality from different sources, the scope seems limited compared to what a comprehensive C2PA/credentials server might offer.
The server only provides read operations from two input sources, missing essential capabilities for a Content Credentials domain. There are no tools for creating, updating, validating, or managing credentials, nor tools to list available manifests or check credential status. This creates significant gaps that would limit agent workflows beyond basic information retrieval.