https://github.com/kyanitelabs/mcp-video
Video editing MCP server for AI agents. 87 FFmpeg and Hyperframes tools, Python client, and CLI. Local, fast, free.
https://github.com/kyanitelabs/mcp-video
agent-tools ai-agents ai-video claude claude-code cli cursor ffmpeg hyperframes mcp mcp-server mcp-tools media-automation model-context-protocol python python-library subtitles video video-automation video-editing
Last synced: 7 days ago
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Video editing MCP server for AI agents. 87 FFmpeg and Hyperframes tools, Python client, and CLI. Local, fast, free.
- Host: GitHub
- URL: https://github.com/kyanitelabs/mcp-video
- Owner: KyaniteLabs
- License: apache-2.0
- Created: 2026-03-21T01:27:25.000Z (2 months ago)
- Default Branch: master
- Last Pushed: 2026-05-19T22:48:43.000Z (13 days ago)
- Last Synced: 2026-05-20T00:47:51.996Z (13 days ago)
- Topics: agent-tools, ai-agents, ai-video, claude, claude-code, cli, cursor, ffmpeg, hyperframes, mcp, mcp-server, mcp-tools, media-automation, model-context-protocol, python, python-library, subtitles, video, video-automation, video-editing
- Language: Python
- Homepage: https://kyanitelabs.github.io/mcp-video/
- Size: 12.7 MB
- Stars: 19
- Watchers: 1
- Forks: 6
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: .github/CODEOWNERS
- Security: SECURITY.md
- Support: SUPPORT.md
- Governance: GOVERNANCE.md
- Roadmap: ROADMAP.md
- Maintainers: MAINTAINERS.md
- Agents: AGENTS.md
Awesome Lists containing this project
README
mcp-video
Guardrailed video editing MCP server for AI agents.
Structured tools for FFmpeg video editing, cinematic prompt planning, media analysis, subtitles, audio, effects, Hyperframes video creation, local repurposing packages, and preflight validation that helps prevent silent bad media output.
Install •
Quick Start •
Agent Workflows •
Tools •
Tool Reference •
AI Discovery •
llms.txt •
MCP Registry
---
## Public Discovery
**mcp-video** is a free, open-source **Model Context Protocol (MCP) server**, Python library, and CLI that gives AI agents a real video-editing surface. It wraps FFmpeg, PUSHING CREATION-style planning, media analysis, quality checks, subtitles, audio generation, effects, Hyperframes 0.5 rendering, local repurposing packages, and guardrails for risky edit parameters behind structured tool schemas.
Best-fit searches:
- video editing MCP server
- AI agent video editing
- FFmpeg MCP tools
- Claude Code video editing
- Cursor MCP video tools
- Python video editing library
- subtitle automation
- reels and shorts automation
- agentic media pipeline
- local AI video workflow
- Hyperframes video creation
- YouTube Shorts repurposing
## Why It Exists
AI agents can write FFmpeg commands, but they should not have to guess flags, parse brittle stderr, or silently publish broken media. mcp-video gives agents typed operations, inspectable tool metadata, structured results, preflight guardrails, and quality checkpoints so a video workflow can be automated and reviewed without turning into shell-command roulette.
Use it when you want an AI assistant to:
- trim, merge, resize, crop, rotate, transcode, or export video;
- add text, subtitles, watermarks, overlays, filters, fades, effects, and transitions;
- extract audio, normalize audio, synthesize audio, add generated audio, or create waveforms;
- detect scenes, make thumbnails, generate storyboards, compare quality, and create release checkpoints;
- scaffold cinematic projects, read STYLE_/NEG_ blocks, parse storyboard tables, and expand shot prompts;
- create new Hyperframes projects, inspect rendered layouts, capture websites, generate local speech, remove backgrounds, and post-process the result with FFmpeg tools;
- repurpose one source video into vertical, horizontal, and square local delivery packages with manifests and review artifacts;
- drive repeatable media workflows from Claude Code, Cursor, Codex-style clients, scripts, or CI.
## Installation
Prerequisite: [FFmpeg](https://ffmpeg.org/) must be installed and available on `PATH`.
```bash
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt install ffmpeg
```
Run without a global install:
```bash
uvx --from mcp-video mcp-video doctor
```
Or install with pip:
```bash
pip install mcp-video
mcp-video doctor
```
Hyperframes tools additionally need Node.js 22+ and a resolvable Hyperframes CLI. Install/pin Hyperframes in the active Node package layout, add `hyperframes` to `PATH`, or set `MCP_VIDEO_HYPERFRAMES_COMMAND`.
## Quick Start
### Claude Code
```bash
claude mcp add mcp-video -- uvx --from mcp-video mcp-video
```
### Claude Desktop
```json
{
"mcpServers": {
"mcp-video": {
"command": "uvx",
"args": ["--from", "mcp-video", "mcp-video"]
}
}
}
```
### Cursor
```json
{
"mcpServers": {
"mcp-video": {
"command": "uvx",
"args": ["--from", "mcp-video", "mcp-video"]
}
}
}
```
Then ask your agent:
> Trim this interview into a 45-second vertical clip, add burned captions, normalize the audio, make a thumbnail, and create a release checkpoint before export.
## Python Client
```python
from mcp_video import Client
editor = Client()
clip = editor.trim("interview.mp4", start="00:02:15", duration="00:00:45")
caption_file = "captions.srt"
editor.ai_transcribe(clip.output_path, output_srt=caption_file)
captioned = editor.subtitles(clip.output_path, subtitle_file=caption_file)
vertical = editor.resize(captioned.output_path, aspect_ratio="9:16")
checkpoint = editor.release_checkpoint(vertical.output_path)
print(checkpoint["thumbnail"])
print(checkpoint["storyboard"])
```
## CLI
```bash
mcp-video info interview.mp4
mcp-video trim interview.mp4 -s 00:02:15 -d 45
mcp-video video-ai-transcribe clip.mp4 --output captions.srt
mcp-video subtitles clip.mp4 captions.srt
mcp-video resize clip.mp4 --aspect-ratio 9:16
mcp-video video-quality-check clip.mp4
mcp-video repurpose clip.mp4 --platforms youtube-shorts instagram-reel tiktok
```
## What Agents Can Do
| Workflow | Example prompt |
| --- | --- |
| Social clips | "Turn this landscape recording into a captioned TikTok and YouTube Short." |
| Podcast production | "Find the strongest segment, trim it, normalize audio, add chapters, and export." |
| Product demos | "Create a short launch video from screenshots, title cards, and voiceover." |
| Cinematic planning | "Create a style pack and storyboard, then render shot prompts for generation." |
| Quality review | "Compare these two exports, make thumbnails, and flag visual or audio problems." |
| Batch automation | "Convert this folder of clips to web-ready MP4 with consistent loudness." |
| Code-created video | "Scaffold a Hyperframes composition, inspect it, render it, then add subtitles and a watermark." |
| Local repurposing | "Turn this master clip into Shorts, Reels, TikTok, and YouTube assets with thumbnails and a manifest." |
## MCP Tools
mcp-video currently registers **119 MCP tools**. The table below summarizes the documented core categories; `search_tools` lets agents discover the exact operation they need without loading every tool description into context.
| Category | Count | Highlights |
| --- | ---: | --- |
| Core video editing | 32 | trim, merge, resize, crop, rotate, convert, overlays, subtitles, export, cleanup, templates, merge-compatibility guardrails |
| Cinematic creation | 4 | project scaffold, style-pack parsing, storyboard parsing, shot prompt expansion |
| AI-assisted media | 11 | transcription, scene detection, upscaling, stem separation, silence removal, color grading |
| Hyperframes | 18 | init, preview, render, snapshots, inspect, catalog, website capture, local TTS, transcription, background removal, diagnostics, benchmark, post-process |
| Repurposing | 2 | dry-run manifests, platform-ready variants, thumbnails, storyboards, release checkpoints |
| Procedural audio | 7 | synthesize, compose, presets, effects, sequences, generated audio, spatial audio, mix-parameter guardrails |
| Visual effects | 8 | vignette, glow, noise, scanlines, chromatic aberration, luma key, mask, shape mask, bounded filter parameters |
| Transitions | 3 | glitch, morph, pixelate |
| Layout and motion | 6 | grid, picture-in-picture, split-screen, animated text, counters, progress bars, auto-chapters, layout mismatch warnings |
| Analysis | 8 | scene detection, thumbnail, preview, storyboard, quality compare, metadata, waveform, release checkpoint |
| Image analysis | 3 | extract colors, generate palettes, analyze product images |
| Discovery | 1 | `search_tools` |
```python
from mcp_video import Client
editor = Client()
matches = editor.search_tools("subtitle")
print(matches["tools"])
```
Full reference: [docs/TOOLS.md](docs/TOOLS.md)
## Agent-Safe Workflow
For autonomous agents, the intended path is inspect, edit, verify, then ask a human to review release artifacts:
```python
from mcp_video import Client
client = Client()
print(client.inspect("trim"))
result = client.pipeline(
[
{"op": "trim", "input": "source.mp4", "start": "00:01:00", "duration": "00:00:45"},
{"op": "add_text", "text": "Launch clip", "position": "top-center"},
{"op": "normalize_audio"},
{"op": "resize", "aspect_ratio": "9:16"},
{"op": "export", "quality": "high"},
{"op": "release_checkpoint"},
],
output_path="final-short.mp4",
)
```
Safety contract:
- Media-producing calls return structured results with output paths.
- High-risk edit paths now run preflight guardrails before FFmpeg execution: filter bounds, merge compatibility, audio mix volume/timing, overlay/watermark/chroma opacity and similarity, animated text timing/overflow, and grid/split-screen mismatch warnings.
- Analysis and discovery calls return structured JSON reports.
- Tool discovery is available through `search_tools()` and `Client.inspect()`.
- Unexpected keyword errors are converted into actionable `MCPVideoError` guidance.
- Do not publish agent-generated video without `video_quality_check`, `video_release_checkpoint`, and human visual/audio inspection.
## Documentation
- [Tool reference](docs/TOOLS.md)
- [Python client reference](docs/PYTHON_CLIENT.md)
- [CLI reference](docs/CLI_REFERENCE.md)
- [AI agent discovery guide](docs/AI_AGENT_DISCOVERY.md)
- [FAQ](docs/faq.md)
- [llms.txt](llms.txt)
## Testing
Development verification lives in [docs/TESTING.md](docs/TESTING.md). Keep public-surface, media workflow, and security checks current when changing tool behavior.
## Development
```bash
git clone https://github.com/KyaniteLabs/mcp-video.git
cd mcp-video
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest tests/ -v -m "not slow and not hyperframes"
```
## Community
- [Contributing](CONTRIBUTING.md)
- [Code of Conduct](CODE_OF_CONDUCT.md)
- [Governance](GOVERNANCE.md)
- [Maintainers](MAINTAINERS.md)
- [Security](SECURITY.md)
- [Support](SUPPORT.md)
- [Roadmap](ROADMAP.md)
- [Changelog](CHANGELOG.md)
- [GitHub Discussions](https://github.com/KyaniteLabs/mcp-video/discussions)
## License
Apache 2.0. See [LICENSE](LICENSE).
Built with [FFmpeg](https://ffmpeg.org/), [Hyperframes](https://hyperframes.io/), and the [Model Context Protocol](https://modelcontextprotocol.io/).