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strip-ai-metadata

Remove hidden metadata from photos, videos, PDFs and camera RAW files: GPS location, camera and serial numbers, author names, dates, XMP/IPTC, C2PA Content Credentials and AI prompts (Stable Diffusion, ComfyUI, Midjourney, ChatGPT, Firefly).

  • Lossless. Metadata is cut out or blanked in place, so image pixels, video streams and RAW sensor data are untouched.

  • Local. Nothing is uploaded.

  • Use it three ways: an MCP server for AI assistants, a CLI, or a Node library.

This is the engine behind the free browser tools at stripaimetadata.com.

Package

What it is

strip-ai-metadata-mcp

A free MCP server for Claude, Cursor and VS Code: "remove the location from the photos in my Downloads folder"

strip-ai-metadata

CLI and Node library: npx strip-ai-metadata photo.jpg video.mp4 report.pdf IMG_0001.CR3

Quick start: Claude Desktop

{
  "mcpServers": {
    "strip-ai-metadata": { "command": "npx", "args": ["-y", "strip-ai-metadata-mcp"] }
  }
}

There are more setups (Claude Code, Cursor, VS Code) in the MCP README and at stripaimetadata.com/mcp.

Related MCP server: docuprivado

Supported formats

Kind

Formats

Removed

Photos

JPG, PNG, WebP, AVIF, HEIC

EXIF, GPS, XMP, IPTC, C2PA, PNG text chunks (prompts, ComfyUI workflows), comments, trailing data

Video

MP4, MOV, M4V, 3GP

GPS and GPS tracks, device, dates, C2PA, XMP, GoPro and DJI telemetry

PDF

PDF

Author, title, software, dates, XMP, page metadata, EXIF inside embedded photos, old revisions

RAW

CR2, CR3, NEF, ARW, DNG, RAF, RW2, ORF, PEF

GPS, body and lens serials, owner, copyright, dates, XMP, IPTC. Make, model and maker notes are kept so raw editors still read the file.

Layout

src/lib/meta/   image engine (JPEG, PNG, WebP, HEIC/AVIF parsing, lossless stripping, AI and C2PA detection)
src/lib/raw.ts  RAW engine (in-place blanking; same size, sensor data untouched)
src/lib/pdf.ts  PDF engine
src/lib/video.ts MP4/MOV engine (edits boxes in place, no re-encode)
packages/       npm packages that bundle the engine
scripts/        tests

Develop

npm install
npm run build   # builds packages/*/dist
npm test        # RAW engine tests

MIT licensed.

Available Tools

2 tools
clean_filesRemove metadata from filesA

Removes hidden metadata from photos (JPG, PNG, WebP, AVIF, HEIC), videos (MP4, MOV), PDFs and camera RAW files (CR2, CR3, NEF, ARW, DNG, RAF, RW2, ORF, PEF): GPS location, camera and serial numbers, owner and author names, dates, XMP/IPTC, C2PA Content Credentials and AI prompts. Works on files or folders on this computer. Originals are not changed: a clean copy is saved as name-clean.ext unless in_place is true. Runs locally; nothing is uploaded.

Inputs: paths (required), mode, in_place, recursive, +2 more.

inspect_filesShow hidden metadata in filesA
Read-only

Lists what photos, videos, PDFs and RAW files reveal without changing them: GPS location, camera, serial numbers, author, dates, C2PA Content Credentials, AI generator tags and AI prompts. Use it to check a file before sharing or to confirm a clean copy is clean.

Inputs: paths (required), recursive.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools are cleanly opposed: clean_files mutates files by stripping metadata, while inspect_files only reports metadata without changing anything. Descriptions explicitly cross-reference the pair (inspect to confirm a clean copy is clean), so an agent can never mistake one for the other.

    Naming Consistency5/5

    Both names follow the same verb_noun snake_case convention (clean_files, inspect_files) and share the _files noun, giving a predictable, uniform pattern.

    Tool Count4/5

    Two tools is on the thin side of the typical range, but for a focused local metadata-stripping utility the inspect+clean pairing is exactly the necessary surface with nothing extraneous. It is minimal rather than bloated.

    Completeness4/5

    The domain lifecycle is covered: inspect before sharing, clean, then inspect again to verify. Minor gaps exist, such as no selective per-tag removal or dry-run/batch summary report, but agents can work around these by re-inspecting cleaned output.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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