TL;DR: This project provides an agent skill and MCP server that bridges coding assistants directly to local FFmpeg and Python. Instead of letting agents guess shell commands or raw filter graphs, it exposes 42 structured tools with typed arguments and self-verification checks.
Best for: Developers using AI coding assistants who need to programmatically process video locally.
Repository snapshot: ⭐ 4 424 stars · 🍴 349 forks · Python · MIT
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What it is

ffmpeg-skill is an open-source Python project that bridges AI coding assistants directly to local video processing tools. It provides an agent skill and server implementation that exposes 42 typed tools for editing media without cloud dependencies.

How it works

The project exposes local media utilities through a machine-readable contract. Instead of letting coding assistants guess command-line flags, it uses typed arguments and self-verification checks. Every editing job runs a mandatory probe phase to measure file properties before executing local operations.

Key features

  • Forty-two local video tools covering cuts, silence removal, captions, and loudness normalisation
  • Model Context Protocol server integration for assistants like Claude Code and Cursor
  • Automated verification using built-in probing and contact sheets
  • Fully offline operation with no cloud dependencies or API keys
  • Runtime input schemas generated from command-line argument definitions

Getting started

Clone the repository from GitHub, ensure you have Python and FFmpeg installed locally, and configure the server inside your coding assistant environment.

When not to use it

Skip this project if you do not use AI coding assistants or if your environment lacks a local installation of Python and FFmpeg.

Discuss

Which video editing task do you find yourself scripting most often in your projects?

Curated from the repository README and metadata. No hands-on test is claimed; evaluate it in a sandbox before production use.