Video editing MCP server for AI agents. 90 tools, 3 interfaces, rich CLI. Local, fast, free.
Project description
mcp-video
Video editing and creation for AI agents.
Edit existing video with FFmpeg. Create new video from code with Hyperframes or Remotion.
Install • Quick Start • Tools • Full Reference • Agent Discovery • Contributing • Changelog
What is mcp-video?
An open-source video editing server built on the Model Context Protocol (MCP). It gives AI agents, developers, and video creators the ability to programmatically edit and create video files.
Two modes:
- Edit existing video with FFmpeg — trim, merge, overlay text, add audio, apply filters, stabilize, detect scenes, transcribe, and more.
- Create new video from code with Hyperframes (HTML-native, Apache 2.0) or Remotion (React/TypeScript) — scaffold compositions, preview live, render to MP4, then post-process.
Three interfaces:
| Interface | Best For | Example |
|---|---|---|
| MCP Server | AI agents (Claude Code, Cursor) | "Trim this video and add a title" |
| Python Client | Scripts, automation, pipelines | editor.trim("v.mp4", start="0:30", duration="15") |
| CLI | Shell scripts, quick ops, humans | mcp-video trim video.mp4 -s 0:30 -d 15 |
Installation
Prerequisites: FFmpeg must be installed. For Hyperframes or Remotion features, you also need Node.js 22+.
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt install ffmpeg
Install:
pip install mcp-video
# or run without installing:
uvx mcp-video
Verify your setup:
mcp-video doctor
mcp-video doctor --json
Quick Start
As an MCP Server (for AI agents)
Claude Code:
claude mcp add mcp-video -- uvx mcp-video
Claude Desktop:
{
"mcpServers": {
"mcp-video": {
"command": "uvx",
"args": ["mcp-video"]
}
}
}
Cursor:
{
"mcpServers": {
"mcp-video": {
"command": "uvx",
"args": ["mcp-video"]
}
}
}
Then just ask your agent: "Trim this video from 0:30 to 1:00, add a title card, and resize for TikTok."
As a Python Library
from mcp_video import Client
editor = Client()
info = editor.info("interview.mp4")
clip = editor.trim("interview.mp4", start="00:02:15", duration="00:00:30")
video = editor.merge(clips=["intro.mp4", clip.output_path, "outro.mp4"])
video = editor.add_text(video.output_path, text="EPISODE 42", position="top-center", size=48)
result = editor.resize(video.output_path, aspect_ratio="9:16")
Agent-safe Python workflow
For autonomous agents, prefer inspection, pipeline chaining, and a release checkpoint:
from mcp_video import Client
client = Client()
print(client.inspect("create_from_images")) # Real params, aliases, return type
result = client.pipeline(
[
{"op": "create_from_images", "images": frames, "fps": 30},
{"op": "effect_glow", "intensity": 0.2}, # safe capped default
{"op": "add_audio", "audio_path": "soundtrack.wav", "mix": True},
{"op": "export", "quality": "high"},
],
output_path="final.mp4",
)
checkpoint = client.release_checkpoint(result.output_path)
print(checkpoint["thumbnail"], checkpoint["storyboard"])
Agent contract:
- Media-producing client calls return
EditResultwith.output_path. - Analysis/discovery calls return typed reports or dictionaries.
Client.inspect(name)exposes parameters, aliases, category, and return type.- Raw unexpected-keyword errors are converted into actionable
MCPVideoErrorguidance. - Do not publish agent-generated video without
assert_quality()orrelease_checkpoint()plus human visual/audio inspection.
As a CLI Tool
mcp-video info video.mp4
mcp-video trim video.mp4 -s 00:02:15 -d 30
mcp-video convert video.mp4 -f webm -q high
mcp-video template tiktok video.mp4 --caption "Check this out!"
MCP Tools
90 unique MCP tools across 12 categories, plus a search_tools meta-tool for fast discovery. All return structured JSON. See the full tool reference for complete details.
| Category | Count | Highlights |
|---|---|---|
| Core Video | 29 | trim, merge, text, audio, resize, convert, filters, stabilize, chroma key, subtitles, watermark, batch, export, normalize audio |
| AI-Powered | 11 | transcribe (Whisper), scene detect, stem separation (Demucs), upscale, color grade |
| Hyperframes | 8 | init, render, still, preview, compositions, validate, add block, pipeline |
| Remotion | 8 | create project, scaffold, render, studio preview, pipeline (deprecated) |
| Audio Synthesis | 7 | generate waveforms, presets, sequences, effects, spatial audio — pure NumPy |
| Visual Effects | 6 | vignette, chromatic aberration, scanlines, noise, glow, mask |
| Transitions | 3 | glitch, pixelate, morph |
| Layout & Motion | 6 | grid, pip, animated text, counters, progress bars, auto-chapters |
| Analysis | 8 | scene detect, thumbnail, preview, storyboard, quality compare, metadata, waveform, release checkpoint |
| Image Analysis | 3 | color extraction, palette generation, product analysis |
| Meta | 1 | search_tools — keyword search across all tools |
Tool discovery:
from mcp_video import Client
editor = Client()
results = editor.search_tools("subtitle") # Find subtitle-related tools
Hyperframes Integration
Create videos programmatically with Hyperframes — an HTML-native framework for video (Apache 2.0).
1. Create project -> hyperframes_init
2. Add blocks -> hyperframes_add_block
3. Preview live -> hyperframes_preview
4. Render -> hyperframes_render
5. Post-process -> hyperframes_to_mcpvideo
See Hyperframes docs and the Python client reference.
Remotion Integration (Deprecated)
⚠️ Remotion is deprecated and will be removed in a future major version. All Remotion tools now emit
DeprecationWarning. Please migrate to Hyperframes (Apache 2.0) or Revideo (MIT).
Create videos programmatically with Remotion — a React framework for video.
1. Create project -> remotion_create_project
2. Scaffold -> remotion_scaffold_template
3. Preview live -> remotion_studio
4. Render -> remotion_render
5. Post-process -> remotion_to_mcpvideo
See Remotion docs and the Python client reference.
Python Client
from mcp_video import Client
editor = Client()
See the full Python client reference for all methods and return types.
CLI Reference
mcp-video [command] [options]
See the full CLI reference for all commands and options.
Timeline DSL
For complex multi-track edits, describe everything in a single JSON object:
editor.edit({
"width": 1080,
"height": 1920,
"tracks": [
{
"type": "video",
"clips": [
{"source": "intro.mp4", "start": 0, "duration": 5},
{"source": "main.mp4", "start": 5, "trim_start": 10, "duration": 30},
{"source": "outro.mp4", "start": 35, "duration": 10},
],
"transitions": [
{"after_clip": 0, "type": "fade", "duration": 1.0},
],
},
{
"type": "audio",
"clips": [
{"source": "music.mp3", "start": 0, "volume": 0.7, "fade_in": 2},
],
},
],
"export": {"format": "mp4", "quality": "high"},
})
Templates
Pre-built templates for common social media formats:
from mcp_video.templates import tiktok_template, youtube_shorts_template
timeline = tiktok_template(video_path="clip.mp4", caption="Check this out!", music_path="bgm.mp3")
result = editor.edit(timeline)
Supports: TikTok, YouTube Shorts, Instagram Reels/Posts, YouTube Videos.
Error Handling
Structured, actionable errors with auto-fix suggestions:
{
"success": false,
"error": {
"type": "encoding_error",
"code": "unsupported_codec",
"message": "Codec error: vp9 — Auto-convert input from vp9 to H.264/AAC before editing",
"suggested_action": {
"auto_fix": true,
"description": "Auto-convert input from vp9 to H.264/AAC before editing"
}
}
}
Workflows
ICM-style staged pipelines for common productions — with CONTEXT.md stage contracts, references/ factory config, and runnable workflow.py scripts.
cd workflows/01-social-media-clip
python workflow.py /path/to/video.mp4
| Workflow | Stages | Description |
|---|---|---|
01-social-media-clip |
5 | Landscape → TikTok / Short / Reel |
02-podcast-clip |
6 | Highlight with chapters + burned captions |
03-explainer-video |
7 | Branded explainer from scratch |
See workflows/CONTEXT.md for the routing table.
Architecture
mcp_video/
client/ # Python Client API (mixins per domain)
client/meta.py # Client discovery mixin (search_tools)
server.py # MCP server (90 tools + 4 resources + search_tools meta-tool)
server_tools_*.py # Tool registration by category
engine.py # Core FFmpeg engine
engine_*.py # Specialized engines (thumbnail, edit, probe, etc.)
models.py # Pydantic models
errors.py # Error hierarchy + FFmpeg stderr parser
ffmpeg_helpers.py # Shared FFmpeg utilities
audio_engine.py # Procedural audio synthesis
effects_engine.py # Visual effects + motion graphics
transitions_engine.py # Clip transitions
ai_engine.py # AI features (Whisper, Demucs, Real-ESRGAN)
hyperframes_engine.py # Hyperframes CLI wrapper
remotion_engine.py # Remotion CLI wrapper (deprecated)
image_engine.py # Image color analysis
quality_guardrails.py # Automated quality checks
workflows/ # ICM staged pipelines
CONTEXT.md # Layer 1 routing table
01-social-media-clip/ # Stage contract + runnable script
02-podcast-clip/ # Stage contract + runnable script
03-explainer-video/ # Stage contract + runnable script
Supported Formats
| Video | Audio (extraction) | Subtitles |
|---|---|---|
| MP4, WebM, MOV, GIF | MP3, AAC, WAV, OGG, FLAC | SRT, WebVTT |
Agent Discovery
llms.txt— compact project map for agentsdocs/AI_AGENT_DISCOVERY.md— richer positioning and integration snippets
Development
git clone https://github.com/pastorsimon1798/mcp-video.git
cd mcp-video
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
Community & Support
- Contributing: CONTRIBUTING.md
- Security: SECURITY.md (private reporting path)
- Help: SUPPORT.md or GitHub Discussions
- Code of Conduct: CODE_OF_CONDUCT.md
- Changelog: CHANGELOG.md
- Roadmap: ROADMAP.md
- Governance: GOVERNANCE.md
- Maintainers: MAINTAINERS.md
Testing
Tests are excluded from the PyPI package. To run locally:
pip install -e ".[dev]"
pytest tests/ -v -m "not slow and not remotion and not hyperframes"
See docs/TESTING.md for full test categories and CI details.
License
Apache 2.0 — see LICENSE.
Built on FFmpeg, Hyperframes, Remotion, and the Model Context Protocol.
See docs/LEGAL_REVIEW.md for dependency licensing notes.
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