ffmpeg-mcp

An MCP (Model Context Protocol) server for AI-agent-driven video editing, powered by FFmpeg.

It exposes FFmpeg as a set of safe, structured tools that an AI agent (Claude Desktop, Claude Code, or any MCP client) can call in natural language — "trim the first 10 seconds", "burn these subtitles in", "transcribe the speech to an SRT", "cut the silent parts".

The server shells out to the installed ffmpeg/ffprobe binaries; there is no FFmpeg source build required.

Requirements

• Node.js ≥ 18
• FFmpeg + ffprobe on your PATH (or set FFMPEG_PATH / FFPROBE_PATH). A full build is recommended (libass, NVENC, whisper). Tested with FFmpeg 8.1.

Install & build

npm install
npm run build

Tools

Tool	What it does
probe	Inspect a file: duration, format, bitrate, streams (codec/resolution/fps/channels).
trim	Cut a segment by start + end/duration. Stream-copy (fast) or re-encode (frame-accurate).
concat	Join clips. copy (same codecs) or reencode (normalize).
convert	Transcode: format/codec/resolution/fps/bitrate. Supports NVENC (h264-nvenc, …).
extract_audio	Pull the audio track out (mp3/aac/wav/flac/opus).
thumbnail	Single frame at a time, or frames every N seconds.
burn_subtitles	Hard-burn an .srt/.ass file onto the video.
overlay	Watermark image / picture-in-picture, with position, scale, opacity.
auto_subtitle	Speech → subtitles via FFmpeg's whisper filter (needs a model — see below).
cut_silence	Detect silent spans and remove them.

All tools resolve relative paths against the working directory (or FFMPEG_MCP_WORKDIR), validate that inputs exist, and refuse to overwrite outputs unless you pass overwrite: true.

Configuration (environment variables)

Var	Purpose
FFMPEG_PATH / FFPROBE_PATH	Full path to the binaries if not on PATH.
FFMPEG_MCP_WORKDIR	Base directory for resolving relative paths.
WHISPER_MODEL_PATH	Default whisper.cpp model file for auto_subtitle.

Whisper model (for auto_subtitle)

The whisper filter needs a ggml-*.bin model (not bundled — it's large). Fetch one with the helper script:

npm run download-model            # downloads ggml-base.bin into ./models
npm run download-model -- small   # or another size: tiny | base | small | medium | large

Then point the server at it via WHISPER_MODEL_PATH (see registration below), or pass model per call. You can also download manually from huggingface.co/ggerganov/whisper.cpp.

Register with Claude

Claude Code

claude mcp add ffmpeg -- node /absolute/path/to/ffmpeg-mcp/dist/index.js

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "ffmpeg": {
      "command": "node",
      "args": ["C:\\absolute\\path\\to\\ffmpeg-mcp\\dist\\index.js"],
      "env": {
        "WHISPER_MODEL_PATH": "C:\\models\\ggml-base.bin"
      }
    }
  }
}

Develop & verify

npm test          # unit + real-ffmpeg E2E tests (fixtures generated by ffmpeg)
npm run inspect   # launch the MCP Inspector against the server

The Inspector lets you call each tool interactively and see the JSON results.

Project structure

src/
  index.ts            # MCP server bootstrap (stdio), tool registration
  ffmpeg/
    locate.ts         # resolve ffmpeg/ffprobe (PATH or env override)
    runner.ts         # spawn wrapper: args-array (no shell), progress, errors
    probe.ts          # ffprobe -> structured metadata
  lib/
    paths.ts          # input/output path validation & overwrite policy
    schema.ts         # shared zod fragments (timecode, resolution)
  tools/              # one file per MCP tool + registry (index.ts)
test/                 # unit tests + real-ffmpeg E2E (fixtures via lavfi)
scripts/
  download-model.mjs  # fetch a whisper ggml model into ./models

Design notes

• No shell interpolation — ffmpeg is always invoked with an argument array, so user-supplied paths cannot inject commands.
• Path safety — inputs must exist; outputs never overwrite unless overwrite: true.
• No FFmpeg build — the server calls the installed binaries; nothing is compiled.

Contributing

Issues and PRs are welcome. Please run npm run build and npm test before opening a PR.

License

MIT © Sohn EuiJin