C2pa Python Packages

remove-ai-watermarks

AI watermark remover. CLI and Python library to strip visible and invisible AI watermarks (Gemini / Nano Banana sparkle, SynthID) and provenance metadata (C2PA, EXIF, IPTC) from images.

deepfake-detector-mcp

Analyze images, videos, and audio for deepfake manipulation artifacts. Checks metadata, provenance chains, and synthesis indicators.

meok-watermark-attest-mcp

EU AI Act Article 50 watermarking compliance MCP — C2PA, content provenance, deepfake disclosure, AI-content labelling. Hits the November 2026 cliff. By MEOK AI Labs.

watermarking-authenticity-mcp

EU AI Act Art.50 watermarking + C2PA 2.1. 2 Dec 2026 deadline. Part of the CSOAI Layer-0: 8 protocols · 100/100 A+++++ · world-leading.

meok-w3c-tdm-rights-mcp

EU CDSM Art 4(3) TDM rights MCP - issues + scans HTTP/HTML/robots/C2PA reservation signals + signs training-run liability shield. MIT. By MEOK AI Labs.

noai-watermark

Remove invisible AI watermarks (SynthID, StableSignature, TreeRing) and strip AI metadata from images. Open-source CLI & Python toolkit.

meok-eu-aigc-icon-mcp

MEOK EU AIGC Icon MCP - EU AI Act Article 50 Code of Practice icon emitter. MIT. By MEOK AI Labs.

c2pa

Python implementation of C2PA: Coalition for Content Provenance and Authenticity.

c2pie

The world's first c2pa standard implementation that supports PDF-files signing.

inclusio

Accessibility-first publishing engine — PDF/UA-2 + WTPDF + PDF/A-4f, C2PA + PAdES + SLSA provenance, multi-format emission, MCP server.

numbers-c2pa

Numbers C2PA tool

rooted-sbr

Open-source, vendor-neutral C2PA Soft Binding Resolution server on Backblaze B2. Recovers stripped provenance for AI image, audio, and video, with a WORM transparency log and an MCP surface.

langchain-chronoverify

Drop-in recipes to give any AI agent image capture-time and provenance verification with ChronoVerify: MCP one-click install, OpenAI/Claude tool defs, LangChain/LlamaIndex/CrewAI/n8n, and REST.

zpe-video

Perception receipts for AI video pipelines. Cross-writer bit-exact under default settings (SHA-256 stable across writers in any language). Zero runtime dependencies; pure stdlib core. ~1.1 KB per video; per-frame CRC32 + schema + versioning. Useful now, improving continuously.