is-it-ai-mcp

An MCP server that reads the C2PA Content Credential embedded in an image and reports what the file declares about its own origin, plus whether that declaration still verifies against the bytes in front of you.

📖 Documentation: mcp.johannsenlum.com/is-it-ai · install guide · tool reference

🔍 Try it without installing anything: ai.johannsenlum.com/is-it-ai runs the same checks in your browser, on your machine, with nothing uploaded.

What it does

It opens an image, looks for an embedded C2PA manifest (a Content Credential), and if one exists, reports two separate things: what the manifest claims about how the image was made, and whether the cryptographic signature over that manifest still matches the file's current bytes. It does not look at pixels and it does not guess. If there is no manifest, or the manifest exists but the signature is broken, it says so plainly instead of inventing an answer.

See docs/pass-fail.md for why "the signature verified" and "the claim is true" are two different questions, and why this server only ever answers the first one.

Related MCP server: image-forensics-mcp

Install

Running the server

is-it-ai-mcp is published on PyPI. Run it with:

uvx is-it-ai-mcp

Install from source (contributors / unreleased main). Not part of the normal install path above, only needed if you want the latest unreleased code instead of the published PyPI release:

uvx --from git+https://github.com/JohannsenLum/is-it-ai-mcp is-it-ai-mcp

Or run from a local clone:

git clone https://github.com/JohannsenLum/is-it-ai-mcp
cd is-it-ai-mcp
uv sync

No account, API key, or environment variable is required. The server only reads local files you point it at.

Claude Code and Claude Desktop

{
  "mcpServers": {
    "is-it-ai": {
      "command": "uvx",
      "args": ["is-it-ai-mcp"]
    }
  }
}

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

Copy this JSON in via Settings → Developer → Edit Config:

{
  "mcpServers": {
    "is-it-ai": {
      "command": "uvx",
      "args": ["is-it-ai-mcp"]
    }
  }
}

Tools

check_image_provenance

Give it the path to one image file on disk. It returns:

• verdict: one of the three states below (AI_DECLARED, NO_AI_DECLARED, UNKNOWN).

• reason: the specific basis for that verdict, for example no-credential, credential-invalid, ai-source-type, capture-source-type, or credential-silent.

• what_this_does_not_mean: a plain-language caveat attached to every verdict, so the result cannot be quietly upgraded into a stronger claim than the evidence supports.

• signature: the raw validation_state, a verified boolean, and any failure_codes the signature check produced.

• declared: what the manifest claims when one exists. signer, claim_generator, and signed_at are free text pulled straight from the file, so each is guarded per the Security section below before it reaches you. source_types (IPTC digital-source-type URIs, drawn from a closed vocabulary) and watermark_declared (a boolean) cannot carry attacker-authored text, so both are returned as-is and are never fenced.

A file that cannot be read (bad path, unsupported format) comes back as a distinct error result rather than a fake UNKNOWN. It needs a real path on disk, not the image bytes themselves. See Note on file paths.

scan_directory

Give it a folder. It walks the tree, runs every image it finds through the same check, and returns aggregate counts by verdict and by signer, plus a capped sample of the files that carried a credential, rather than a line per file. This is the tool that reproduces this project's own 401-image sweep (see below) against any directory you point it at.

The three verdicts

UNKNOWN is the default and by far the most common answer. In a scan of 401 real images, only 14 carried a Content Credential at all, and every one of those was from OpenAI: about 96.5% had no credential whatsoever. Expect UNKNOWN on almost everything you check. That is not a bug in this server, it is the current state of image provenance in the wild.

What this cannot tell you

• It does not detect AI from pixels. There is no image analysis here at all, no model looking at the picture. Every verdict comes from a cryptographically signed text record, or from the absence of one.

• A missing credential is not evidence of anything. An unmarked AI image and an unmarked photograph are indistinguishable to this tool. Screenshotting, re-saving, or passing an image through almost any editor strips the credential, AI-made or not. UNKNOWN means "no usable record survived," never "no AI was involved."

• A valid signature does not make the signer's claims true. The signature proves the manifest has not been altered since it was signed and confirms who signed it. It proves nothing about whether the signer told the truth. Anyone can generate their own certificate, sign their own file, and assert whatever origin they like: it will verify perfectly and still be false. Verification is about the seal, not the letter. See docs/pass-fail.md.

Why it exists

When you attach an image to a model, the image is decoded to pixels and re-encoded before the model ever sees it. Container metadata, including any C2PA manifest, never reaches the model: the model sees an RGB array, nothing more. Without a tool, it cannot read a manifest at all, and it will tend to guess whether an image is AI-generated from visual artefacts instead. Published benchmarks put that guess at roughly 18 to 31% accuracy, little better than chance. This server exists so the model reads the actual signed record on disk instead of pattern-matching on JPEG compression artefacts.

Security

Every human-readable string returned by this server originated inside the file being inspected: signer name, claim-generator string, and any free-text reason or label. That text was written by whoever produced the file, not by you, and it lands in the same context window as your own instructions. A field labelled "signer" carries an air of verified authority, but the signature covers the asset's bytes, not the honesty of any string inside the manifest. Anyone can sign their own file with their own certificate and write anything they like in it.

Before any such string is returned, it is cleaned of control characters, length-capped, and wrapped in a fenced boundary that marks it explicitly as untrusted data rather than instructions, with a random nonce the file's author could not have pre-guessed. Structural values, the verdict itself, the validation state, and the IPTC source-type URIs are drawn from closed vocabularies this server controls and are never fenced, since they cannot carry attacker-authored text.

See src/is_it_ai_mcp/safety.py for the implementation and the full threat model in its module docstring.

Note on file paths

This tool takes a file path, not image bytes. In Claude Code, an image you paste into the conversation is written to disk first, so its path is reachable and this just works. In other clients, a pasted or attached image may exist only as inline data with no path on the filesystem the server can reach, in which case there is nothing for this tool to open. If a check comes back unable to find the file, save the image to disk first and point the tool at that path.

Development

uv sync --extra dev
uv run pytest -v

--extra dev matters: without it, pytest-asyncio (needed for asyncio_mode = "auto" in pyproject.toml) is not installed, and pytest prints an "Unknown config option: asyncio_mode" warning on every run.

Tests run against the fixtures in fixtures/, a real signed image plus tampered and stripped variants with hand-verified expected outcomes. See fixtures/GROUND-TRUTH.md for how each was produced and what each is expected to prove.

Licence

MIT © 2026 Johannsen Lum.

Use it, change it, redistribute it, build something commercial on it: the only condition is that you keep the copyright notice and licence text. It comes with no warranty of any kind.

Contributions are accepted under the same licence.