#ffmpeg

Botverse gives AI agents a one-call API for video transcoding and document conversion. Transcode to MP4, WebM/VP9, ProRes 422, GIF, or MP3; convert PDFs, DOCX, PPTX, images, and HTML. Prepaid wallet with per-job billing — no FFmpeg, no storage, no infrastructure.

MCP server to run FFmpeg commands on our infrastructure. See documentation here: https://verygoodffmpeg.com/docs/integrations/mcp-server

Podcli is an open-source MCP server and CLI that turns long-form podcasts into upload-ready short clips for TikTok, YouTube Shorts, and Reels. It transcribes with Whisper, finds viral moments with Claude or Codex against your show's knowledge base, crops to vertical with face tracking, and burns in captions in four styles. Ships 17 MCP tools you can plug into Claude Code, Claude Desktop, or Codex — ask the agent to "clip this episode" and it handles transcription, clip scoring, and export end to end. Runs fully locally, no uploads, no API keys required unless you opt into AI clip picking. MIT licensed.

这是一个基于 Model Context Protocol (MCP) 的 FFmpeg 视频音频处理服务器。该项目为 AI 助手提供了强大的视频和音频处理能力，包括格式转换、切割合并、特效添加等功能，支持硬件加速处理。

mcp-ffmpeg-tools is an open-source Python MCP (Model-Command Protocol) server that enables LLMs to perform media processing tasks by interpreting natural language instructions. It automatically generates and executes FFmpeg commands, then validates results using `ffprobe` or screenshots. The tool also supports querying FFmpeg source code to verify command correctness, making it ideal for intelligent, language-driven media workflows across platforms.

An MCP server for FFmpeg

mcp-ffmpeg: resize videos, extract audio.

Model Context Protocol Server to facilitate llms to able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created.