mcp-ffmpeg
# 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
- **Extract video transcript** - Extracts the transcript of a 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](#configuration)).
## Installation
Choose one of the following:
### Option 1: Install from PyPI
```bash
pip install mcp-ffmpeg
```
Or with [uv](https://docs.astral.sh/uv/):
```bash
uv add mcp-ffmpeg
```
### Option 2: Clone the repository
```bash
git clone https://github.com/priyanshum143/MCP-FFMPEG.git
cd MCP-FFMPEG
```
Then install from the project root:
```bash
# With uv
uv sync
# Or with pip (editable install)
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)
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.
**If you installed from PyPI:**
```bash
mcp-ffmpeg-cli
```
**If you cloned the repo:**
```bash
# With uv (from project root)
uv run python -m MCP_ffmpeg.main
# Or after pip install -e .
mcp-ffmpeg-cli
```
### MCP server (e.g. Claude Desktop)
Use the `mcp-ffmpeg` command so the MCP server runs over stdio.
**If you installed from PyPI:** use `mcp-ffmpeg` in your MCP config.
**If you cloned the repo:** after `pip install -e .`, use `mcp-ffmpeg` the same way. If you used `uv sync`, use `uv run mcp-ffmpeg` in the terminal, or in your MCP config use the path to your venv’s `mcp-ffmpeg` script so the server runs in that environment.
Add this to your `%APPDATA%\Claude\claude_desktop_config.json` (Windows) or the equivalent config for your MCP client:
```json
{
"mcpServers": {
"mcp-ffmpeg": {
"command": "mcp-ffmpeg",
"env": {
"FFMPEG_PATH": "C:\\path\\to\\your\\ffmpeg.exe"
}
}
}
}
```
On macOS/Linux, use your normal config path and set `FFMPEG_PATH` to the path of your `ffmpeg` binary if needed.
## 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
- **GitHub**: [priyanshum143](https://github.com/priyanshum143)
- **LinkedIn**: [Priyanshu Mehta](https://www.linkedin.com/in/priyanshu-mehta-a40799238/)
- **Project Repository**: [MCP-FFMPEG](https://github.com/priyanshum143/MCP-FFMPEG)
- **PyPi**: [MCP-FFmpeg](https://pypi.org/project/mcp-ffmpeg/)
Feel free to reach out for collaborations or if you encounter any issues!
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: status retrieval, result retrieval, and separate processing jobs for audio extraction, format change, resolution change, subtitle format change, trimming, and transcription. No overlap in functionality.
All tools follow a consistent verb_noun pattern: get_ for retrieval and start_ for job enqueuing. Underscores are used uniformly, making the naming predictable.
With 8 tools, the server covers a reasonable set of common FFmpeg operations without being overwhelming. The count is well-scoped for a media processing server.
The tool set covers core operations like status check, result retrieval, audio extraction, format conversion, resolution change, subtitle conversion, trimming, and transcription. Missing tools for video compression, frame extraction, or concatenation, but these are minor gaps given the common use cases.