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A Model Context Protocol server for FFmpeg media processing

Project description

MCP-FFMPEG

An MCP (Model Context Protocol) server and CLI for running FFmpeg jobs via a job queue with configurable parallel workers.

Features

  • Job queue — Enqueue video jobs; workers process them in the background.
  • Parallel workers — Run multiple jobs at once (number set in config).
  • Two interfaces
    • CLI — Interactive menu to pick an action and enter parameters.
    • MCP server — Tools for AI assistants (e.g. Claude Desktop) to enqueue and check jobs.
  • Actions
    • Trim — Cut a segment from a video (start time + duration).
    • Change video format — Convert to another container (e.g. mp4 → mkv) without re-encoding.
    • Change resolution — Convert to another resolution, height and width provided by user.
    • Change Subtitle format — Convert to another subtitle format (e.g. srt -> vtt).
    • Extract Audio - Extract audio from an input video file
  • Caching — Same inputs produce the same job ID; completed jobs are reused unless force_run is used.

Requirements

  • Python 3.13+
  • FFmpeg — Must be on your system PATH or set via FFMPEG_PATH (see Configuration).

Installation

From the project root:

# With uv
uv sync

# Or with pip
pip install -e .

Configuration

  • FFmpeg path

    • Default: use ffmpeg from system PATH.
    • Optional: set env var FFMPEG_PATH to the full path of the FFmpeg executable (e.g. for Claude Desktop).
  • Worker and paths
    Edit src/MCP_ffmpeg/utils/variables.py (class CommonVariables):

    • PARALLEL_EXECUTIONS_ALLOWED — Number of jobs that can run at once (default: 3).
    • WORKER_RE_RUN_TIME — Seconds to wait between queue checks (default: 10).
    • OUTPUT_DIR / LOGS_DIR — Where job outputs and logs are stored (default: outputs/ and logs/ under project root).

Running

CLI (interactive)

# From project root (with src on PYTHONPATH)
uv run python -m MCP_ffmpeg.main

# Or after pip install
python -m MCP_ffmpeg.main

You get a menu: choose an action, enter the requested parameters. Jobs are enqueued and processed by background workers. Logs show which worker picked which job.

Claude Desktop Integration

Add this to your %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-ffmpeg": {
      "command": "mcp-ffmpeg",
      "env": {
        "FFMPEG_PATH": "C:\\path\\to\\your\\ffmpeg.exe"
      }
    }
  }
}

Project layout

src/MCP_ffmpeg/
├── main.py           # CLI entrypoint
├── mcp_server.py     # MCP server entrypoint + tool definitions
├── actions/          # FFmpeg actions (trim, change format)
├── jobs/             # Job queue, manager, worker
└── utils/            # Logging, paths, CLI helpers
  • outputs/ — One folder per job (by job ID), containing job_details.json, output file, and optional ffmpeg_logs.log.
  • logs/ — Application logs.

License

No license required, Clone/Fork the repo and enjoy.

Author

Priyanshu CSE 2025 Graduate | Software Engineer at Amagi Media Labs

Feel free to reach out for collaborations or if you encounter any issues!

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