Enables LLMs to perform FFmpeg operations like clipping, merging, extracting audio, adding subtitles, and transcoding videos via a set of tools exposed as an MCP server.
An MCP server that exposes FFmpeg as structured tools for AI-agent-driven video editing, enabling operations like trimming, subtitling, and transcoding via natural language.
An MCP server that exposes FFmpeg as a structured tool set for AI agents, enabling timeline-based video editing, preview, rendering, and analysis with an optional LLM autopilot.
A lightweight server that exposes FFmpeg's video processing capabilities to AI assistants through the Model Context Protocol (MCP), supporting operations like video format conversion, audio extraction, and adding watermarks.
An MCP server that provides 17 FFmpeg-based tools for video and audio processing, including conversion, compression, and editing. It enables AI assistants to perform complex media tasks like extracting audio, adding watermarks, and merging videos using natural language.