Ffmpeg MCP Server

Parallel video rendering tools: detect GPU encoders, render, color grade, merge audio, concat.

Local serverstdio

What is the Ffmpeg MCP server?

Parallel video rendering tools: detect GPU encoders, render, color grade, merge audio, concat. That is what the ffmpeg mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

Parallel video rendering with live dashboard, GPU auto-detection, checkpoint system, and stream-copy concat. Includes an MCP server, a Claude Code skill, and a CLI.

  • Parallel rendering — Split frames across N worker threads, concat with zero re-encoding
  • GPU auto-detection — Probes NVENC, VideoToolbox, AMF, VA-API, QSV with 1-frame validation
  • Live dashboard — Auto-opens in your browser with per-worker progress, FPS chart, ETA
  • Checkpoint system — 93% reduction in fast-forward overhead for long renders
  • Color grading — 5 built-in presets (noir, warm, cool, cinematic, vintage) plus custom filters
  • Audio merge — Combine video + audio with loudness normalization, no video re-encode

The tools it exposes

The server publishes 7 tools. What each one is for:

  • detect_gpu — Probe hardware encoders (NVENC, VideoToolbox, AMF, VA-API, QSV)
  • system_info — Show CPU cores, RAM, recommended workers, ffmpeg version
  • render_video — Parallel render with live dashboard, progress notifications, and cancellation
  • get_worker_template — Return the worker contract plus the bundled reference worker source
  • color_grade — Apply presets (noir, warm, cool, cinematic, vintage) or custom filters
  • merge_audio — Combine video + audio with loudness normalization
  • concat_videos — Stream-copy join multiple videos (instant, no re-encode), validated by default

What it needs from you

  • Node.js >= 18 - ffmpeg installed and on PATH (or pointed to via env var, below)

Getting it running

The server ships on npm as ffmpeg-render-pro, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.

How it compares

Among the browser automation options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Ffmpeg's toolset — detect_gpu, system_info, render_video and 4 more — is a fair guide to whether it matches your workflow. It is maintained by beeswaxpat; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Ffmpeg's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Available tools

ToolWhat it does
detect_gpuProbe hardware encoders (NVENC, VideoToolbox, AMF, VA-API, QSV)
system_infoShow CPU cores, RAM, recommended workers, ffmpeg version
render_videoParallel render with live dashboard, progress notifications, and cancellation
get_worker_templateReturn the worker contract plus the bundled reference worker source
color_gradeApply presets (noir, warm, cool, cinematic, vintage) or custom filters
merge_audioCombine video + audio with loudness normalization
concat_videosStream-copy join multiple videos (instant, no re-encode), validated by default

How to install the Ffmpeg MCP server

{
  "mcpServers": {
    "ffmpeg-render-pro": {
      "command": "npx",
      "args": ["-y", "ffmpeg-render-pro"]
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

  • Node.js >= 18 - ffmpeg installed and on PATH (or pointed to via env var, below)

Example prompts to try

  • Use Ffmpeg to detect gpu.
  • Use Ffmpeg to system info.
  • Use Ffmpeg to render video.

Frequently asked questions

It connects Ffmpeg to MCP-compatible AI assistants such as Claude and Cursor, exposing 7 tools (detect_gpu, system_info, render_video, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Ffmpeg directly.