auth-securityai-ml

Proofly (Deepfake Detection)▌

by prooflie

Enable advanced deepfake detection in images using Proofly API. Get real/fake probability scores with cutting-edge deepf

Enables deepfake detection in images through Proofly API integration, providing detailed analysis results including real/fake probability scores and individual model results for each detected face.

github stars

★ 1

GitHub npm

Remote — zero setup requiredMultiple deployment options (SSE streaming or HTTP)Per-face detailed analysis

best for

/ Content moderation and verification
/ Security teams validating user-submitted images
/ Media organizations fact-checking photos
/ Developers building authentication systems

capabilities

/ Analyze images from URLs for deepfake detection
/ Process base64-encoded images for face authenticity
/ Get detailed face-by-face analysis results
/ Check analysis session status and progress
/ Generate real/fake probability scores per face

what it does

Detects deepfakes and face swaps in images by analyzing faces and providing probability scores for authenticity. Works with both image URLs and base64-encoded images.

about

Proofly (Deepfake Detection) is an official MCP server published by prooflie that provides AI assistants with tools and capabilities via the Model Context Protocol. Enable advanced deepfake detection in images using Proofly API. Get real/fake probability scores with cutting-edge deepf It is categorized under auth security, ai ml. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Proofly (Deepfake Detection) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Proofly (Deepfake Detection) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Proofly MCP Integration

Install and just write 'proofly it' URL to content or analyze it URL to content for deepfake face swap analysis.

For clients that connect to MCP servers using a URL (e.g., Cursor, Cascade/Windsurf)

Add one of the following configurations to your MCP client (e.g., in mcp_config.json):

A. Streaming (SSE - Recommended where supported):

{
  "proofly": {
    "serverUrl": "https://mcp.proofly.ai/sse",
    "supportedMethods": [
      "analyze-image",
      "analyze",
      "get-face-details",
      "check-session-status"
    ],
    "auth": { "type": "none" } // Or your specific auth if Proofly API https:/get.proofly.ai requires it
  }
}

B. Standard HTTP (Non-streaming):

{
  "proofly": {
    "serverUrl": "https://mcp.proofly.ai/mcp",
    "supportedMethods": [
      "analyze-image",
      "analyze",
      "get-face-details",
      "check-session-status"
    ],
    "auth": { "type": "none" } // Or your specific auth if Proofly API https:/get.proofly.ai requires it
  }
}

For clients that can execute a local command for an MCP server (e.g., Claude Desktop)

Claude Desktop:

Run: npx proofly-mcp@latest
Add to your Claude Desktop config file (e.g., claude_desktop_config.json)

{
  "mcpServers": {
    "proofly": {
      "command": "npx",
      "args": [
        "-y", // The -y flag might be specific to your npm/npx version or aliasing for auto-confirmation.
        "proofly-mcp@latest"
      ],
      "supportedMethods": [
        "analyze-image",
        "analyze",
        "get-face-details",
        "check-session-status"
      ]
    }
  }
}

Alternatively, if you have proofly-mcp installed globally (npm install -g proofly-mcp), you can use:

{
  "mcpServers": {
    "proofly": {
      "command": "proofly-mcp",
      "args": [],
      "supportedMethods": [
        "analyze-image",
        "analyze",
        "get-face-details",
        "check-session-status"
      ]
    }
  }
}

Other command-capable MCP Clients:

If your MCP client can launch a local command, configure it to run proofly-mcp. Conceptual example (actual config varies by client):

{
  "mcpServers": {
    "proofly": {
      "type": "command",
      "command": "proofly-mcp",
      "supportedMethods": [
        "analyze-image",
        "analyze",
        "get-face-details",
        "check-session-status"
      ]
    }
  }
}

Environment Variables for `proofly-mcp` CLI (Optional)

PROOFLY_API_KEY: Your Proofly API key. The proofly-mcp CLI will use this API key if the variable is set when communicating with Proofly API https://get.proofly.ai.

Available MCP Methods

analyze

Analyzes an image from a URL for deepfake detection.

analyze-image

Analyzes an image provided as a base64 string for deepfake detection.

check-session-status

Checks the status of a deepfake analysis session.

get-face-details

Gets detailed information about a specific face detected in an image analysis session.