Image Forensics MCP Server

An MCP (Model Context Protocol) server that gives AI assistants forensic analysis capabilities to help detect AI-generated images. Uses noise maps, Error Level Analysis, FFT frequency analysis, spectral decay analysis, color channel analysis, and metadata inspection.

Install

One command — requires uv:

claude mcp add -s user image-forensics -- uvx --from git+https://github.com/surewht/image-forensics-mcp image-forensics-mcp

That's it. Restart Claude Code and the tools are available.

Alternative: install from local clone

git clone https://github.com/surewht/image-forensics-mcp.git
cd image-forensics-mcp
claude mcp add -s user image-forensics -- uvx --from . image-forensics-mcp

Manual config

Add to ~/.claude.json:

{
  "mcpServers": {
    "image-forensics": {
      "type": "stdio",
      "command": "uvx",
      "args": ["--from", "git+https://github.com/surewht/image-forensics-mcp", "image-forensics-mcp"]
    }
  }
}

Related MCP server: Gemini Image MCP

Tools

Usage

In Claude Code, just ask:

Analyze this image for AI generation: /path/to/image.jpg

Or use individual tools:

Run a noise map analysis on /path/to/image.png
Check the metadata of /path/to/image.webp

How the verdict works

The full_forensic_report categorizes findings into three tiers:

Verdict scale

• AI-GENERATED — Definitive metadata proof found

• LIKELY AI-GENERATED — 3+ strong forensic anomalies

• POSSIBLY AI-GENERATED — 1-2 strong anomalies

• INCONCLUSIVE — Only weak/ambiguous indicators

• LIKELY AUTHENTIC — Minimal indicators, consistent with normal processing

• NO INDICATORS — Clean across all analyses

Limitations

Modern AI generators (Flux, DALL-E 3, Midjourney v6+) produce images that are nearly indistinguishable from real photos at the pixel level. This tool works best when:

• Metadata is intact — SD parameters, generation prompts = definitive proof

• Images show GAN artifacts — periodic patterns in FFT = strong signal

• Images haven't been re-compressed — social media platforms strip metadata and resize to AI-typical dimensions, creating ambiguity

For ambiguous cases, visual inspection (teeth, hands, text, reflections, lighting inconsistencies) combined with these forensic tools gives the best results.

Requirements

• Python >= 3.10

• uv (for uvx install method)

Dependencies (installed automatically): mcp[cli], Pillow, numpy, scipy

License

MIT