pastorsimon1798/mcp-video

pastorsimon1798/mcp-video

MCP for video editing through ffmpeg

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README

<p align="center"> <img src="https://img.shields.io/badge/version-0.4.1-blue.svg" alt="Version"> <img src="https://img.shields.io/badge/tests-396%20passed-brightgreen.svg" alt="Tests"> <a href="https://github.com/pastorsimon1798/mcp-video/actions/workflows/ci.yml"><img src="https://img.shields.io/github/actions/workflow/status/pastorsimon1798/mcp-video/.github/workflows/ci.yml?branch=master&label=CI" alt="CI"></a> <a href="https://glama.ai/mcp/servers/pastorsimon1798/mcp-video"><img src="https://glama.ai/mcp/servers/pastorsimon1798/mcp-video/badges/score.svg" alt="Glama Score"></a> <img src="https://img.shields.io/badge/pypi-mcp--video-blue.svg" alt="PyPI"> <img src="https://img.shields.io/badge/tools-29%20MCP%20tools-orange.svg" alt="Tools"> <img src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" alt="License"> <img src="https://img.shields.io/badge/python-3.11+-blue.svg" alt="Python"> </p>

<h1 align="center">mcp-video</h1>

<p align="center"> <strong>The video editing MCP server for AI agents and humans.</strong><br> 26 tools. 3 interfaces. Rich CLI. Purpose-built for AI agents. </p>

<p align="center"> <a href="#quick-start">Quick Start</a> • <a href="#mcp-tools">Tools</a> • <a href="#python-client">Python API</a> • <a href="#cli">CLI</a> • <a href="#timeline-dsl">Timeline DSL</a> • <a href="#templates">Templates</a> • <a href="ROADMAP.md">Roadmap</a> • <a href="CONTRIBUTING.md">Contributing</a> </p>

What is mcp-video?

mcp-video is 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 video files.

Think of it as ffmpeg with an API that AI agents can actually use. Instead of memorizing cryptic command-line flags, an agent calls structured tools with clear parameters and gets structured results back — or a human uses the rich CLI with spinners, tables, and error panels.

The Problem It Solves

AI agents can write code, analyze documents, and browse the web — but they can't edit video. Existing video editing tools are either:

  • GUI-only (Premiere, DaVinci, CapCut) — agents can't use them
  • Raw FFmpeg wrappers — require memorizing hundreds of flags
  • Cloud APIs (Render, Bannerbear) — expensive, slow, vendor lock-in

mcp-video bridges this gap. It's a local, fast, free video editing layer that any AI agent can use through a standard protocol.

Three Ways to Use It

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

Install

Prerequisites

FFmpeg must be installed on your system:

# macOS
brew install ffmpeg

# For full text overlay support (drawtext filter):
# brew install freetype harfbuzz
# brew reinstall --build-from-source ffmpeg
# Verify: ffmpeg -filters | grep drawtext

# Ubuntu/Debian
sudo apt install ffmpeg

# Windows
# Download from https://ffmpeg.org/download.html

Installation

pip install mcp-video

Or with UVX (no install needed):

uvx mcp_video

Quick Start

1. As an MCP Server (for AI agents)

Install FFmpeg first, then pick your client:

Claude Code:

claude mcp add mcp-video -- pip install mcp-video && mcp-video --mcp

Claude Desktop — add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-video": {
      "command": "uvx",
      "args": ["mcp_video"]
    }
  }
}

Cursor — add to your .cursor/mcp.json:

{
  "mcpServers": {
    "mcp-video": {
      "command": "uvx",
      "args": ["mcp_video"]
    }
  }
}

Any MCP client — if installed via pip, the command is just mcp-video.

Then just ask your agent: "Trim this video from 0:30 to 1:00, add a title card, and resize for TikTok."

2. As a Python Library

from mcp_video import Client

editor = Client()

# Get video info
info = editor.info("interview.mp4")
print(f"Duration: {info.duration}s, Resolution: {info.resolution}")

# Trim a clip
clip = editor.trim("interview.mp4", start="00:02:15", duration="00:00:30")

# Merge clips with transitions
video = editor.merge(
    clips=["intro.mp4", clip.output_path, "outro.mp4"],
    transitions=["fade", "dissolve", "fade"],
)

# Add text overlay
video = editor.add_text(
    video=video.output_path,
    text="EPISODE 42: The Future of AI",
    position="top-center",
    size=48,
)

# Add background music
video = editor.add_audio(
    video=video.output_path,
    audio="music.mp3",
    volume=0.7,
    fade_in=2.0,
    fade_out=3.0,
)

# Resize for TikTok (9:16)
video = editor.resize(video=video.output_path, aspect_ratio="9:16")

# Export final video
result = editor.export(video.output_path, quality="high")
print(result)
# EditResult(output_path='interview_9:16.mp4', duration=45.0, resolution='1080x1920', ...)

3. As a CLI Tool

The CLI outputs rich formatted tables, spinners, and styled error panels by default. Add --format json for scripted/pipe-friendly JSON output.

# Show version
mcp_video --version

# Get video metadata (rich table output)
mcp_video info video.mp4

# Same, but as JSON for scripts
mcp_video --format json info video.mp4

# Generate a fast low-res preview
mcp_video preview video.mp4

# Extract storyboard frames for review
mcp_video storyboard video.mp4 -n 12

# Trim a clip
mcp_video trim video.mp4 -s 00:02:15 -d 30 -o trimmed.mp4

# Convert to a different format
mcp_video convert video.mp4 -f webm -q high

# List available templates
mcp_video templates

# Apply a TikTok template with caption
mcp_video template tiktok video.mp4 --caption "Check this out!"

MCP Tools

mcp-video exposes 29 tools for AI agents. All tools return structured JSON with success, output_path, and operation metadata. On failure, they return {"success": false, "error": {...}} with auto-fix suggestions.

New in v0.4.0: Video reverse playback, green screen / chroma key removal, denoise and deinterlace filters, and smarter GIF output with quality-based scaling.

New in v0.3.0: Video filters & effects (blur, sharpen, color grading with presets), audio normalization to LUFS targets, picture-in-picture and split-screen compositing, and batch processing for multi-file workflows.

Video Operations

Tool Description Key Parameters
video_info Get video metadata input_path
video_trim Trim clip by timestamp input_path, start, duration/end
video_merge Concatenate multiple clips clips[], transitions[], transition_duration
video_speed Change playback speed input_path, factor (0.5=slow, 2.0=fast)
video_reverse Reverse video and audio playback input_path

Effects & Overlays

Tool Description Key Parameters
video_add_text Overlay text/title input_path, text, position, size, color
video_add_audio Add or replace audio video_path, audio_path, volume, mix
video_subtitles Burn SRT/VTT subtitles input_path, subtitle_path
video_watermark Add image watermark input_path, image_path, position, opacity
video_crop Crop to rectangular region input_path, width, height, x?, y?
video_rotate Rotate and/or flip video input_path, angle, flip_horizontal, flip_vertical
video_fade Video fade in/out input_path, fade_in, fade_out
video_chroma_key Remove solid color background (green screen) input_path, color, similarity, blend

Format & Quality

Tool Description Key Parameters
video_resize Change resolution/aspect ratio input_path, width/height or aspect_ratio
video_convert Convert format input_path, format (mp4/webm/gif/mov)
video_export Render with quality settings input_path, quality, format

Filters & Effects

Tool Description Key Parameters
video_filter Apply visual filter (blur, sharpen, grayscale, sepia, invert, vignette, brightness, contrast, saturation, denoise, deinterlace) input_path, filter_type, params
video_blur Blur video input_path, radius, strength
video_color_grade Apply color preset (warm, cool, vintage, cinematic, noir) input_path, preset

Audio

Tool Description Key Parameters
video_normalize_audio Normalize loudness to LUFS target input_path, target_lufs (-16 YouTube, -23 broadcast, -14 Spotify)

Composition

Tool Description Key Parameters
video_overlay Picture-in-picture overlay background_path, overlay_path, position, width, opacity
video_split_screen Side-by-side or top/bottom layout left_path, right_path, layout

Batch Processing

Tool Description Key Parameters
video_batch Apply operation to multiple files inputs[], operation, params, output_dir

Analysis & Extraction

Tool Description Key Parameters
video_thumbnail Extract a single frame input_path, timestamp
video_preview Generate fast low-res preview input_path, scale_factor
video_storyboard Extract key frames as grid input_path, frame_count
video_extract_audio Extract audio track input_path, format (mp3/wav/aac/ogg/flac)

Advanced

Tool Description Key Parameters
video_edit Full timeline-based edit timeline (JSON DSL — see below)

MCP Resources

Resource URI Description
mcp-video://video/{path}/info Video metadata as JSON
mcp-video://video/{path}/preview Key frame timestamps
mcp-video://video/{path}/audio Audio track info
mcp-video://templates Available templates, presets, and formats

Python Client API

Full reference for the Client class:

from mcp_video import Client
editor = Client()

Methods

Method Returns Description
info(path) VideoInfo Video metadata (duration, resolution, codec, fps, size)
trim(input, start, duration?, end?, output?) EditResult Trim by start time + duration or end time
merge(clips, output?, transitions?, transition_duration?) EditResult Concatenate clips with per-pair transitions
add_text(video, text, position?, font?, size?, color?, shadow?, start_time?, duration?, output?) EditResult Overlay text on video
add_audio(video, audio, volume?, fade_in?, fade_out?, mix?, start_time?, output?) EditResult Add or replace audio track
resize(video, width?, height?, aspect_ratio?, quality?, output?) EditResult Resize or change aspect ratio
convert(video, format?, quality?, output?) EditResult Convert format (mp4/webm/gif/mov)
speed(video, factor?, output?) EditResult Change playback speed
thumbnail(video, timestamp?, output?) ThumbnailResult Extract single frame
preview(video, output?, scale_factor?) EditResult Fast low-res preview
storyboard(video, output_dir?, frame_count?) StoryboardResult Key frames + grid
subtitles(video, subtitle_file, output?) EditResult Burn subtitles into video
watermark(video, image, position?, opacity?, margin?, output?) EditResult Add image watermark
crop(video, width, height, x?, y?, output?) EditResult Crop to rectangular region
rotate(video, angle?, flip_horizontal?, flip_vertical?, output?) EditResult Rotate and/or flip video
fade(video, fade_in?, fade_out?, output?) EditResult Video fade in/out effect
export(video, output?, quality?, format?) EditResult Render with quality settings
edit(timeline, output?) EditResult Execute full timeline edit from JSON
extract_audio(video, output?, format?) EditResult Extract audio as file path
filter(video, filter_type, params?, output?) EditResult Apply visual filter (blur, sharpen, grayscale, etc.)
blur(video, radius?, strength?, output?) EditResult Blur video
color_grade(video, preset?, output?) EditResult Apply color preset (warm, cool, vintage, etc.)
normalize_audio(video, target_lufs?, output?) EditResult Normalize audio to LUFS target
overlay(background, overlay, position?, width?, opacity?, start_time?, duration?, output?) EditResult Picture-in-picture overlay
split_screen(left, right, layout?, output?) EditResult Side-by-side or top/bottom layout
reverse(video, output?) EditResult Reverse video and audio playback
chroma_key(video, color?, similarity?, blend?, output?) EditResult Remove solid color background (green screen)
batch(inputs, operation, params?) dict Apply operation to multiple files

Return Models

VideoInfo(path, duration, width, height, fps, codec, audio_codec, ...)
# .resolution  -> "1920x1080"
# .aspect_ratio -> "16:9"
# .size_mb -> 5.42

EditResult(success=True, output_path, duration, resolution, size_mb, format, operation)

ThumbnailResult(success=True, frame_path, timestamp)

StoryboardResult(success=True, frames=["f1.jpg", ...], grid="grid.jpg", count=8)

CLI Reference

mcp_video [command] [options]

Commands:
  info           Get video metadata
  trim           Trim a video
  merge          Merge multiple clips
  add-text       Overlay text on a video
  add-audio      Add or replace audio track
  resize         Resize or change aspect ratio
  convert        Convert video format
  speed          Change playback speed
  thumbnail      Extract a single frame
  preview        Generate fast low-res preview
  storyboard     Extract key frames as storyboard
  subtitles      Burn subtitles into video
  watermark      Add image watermark
  crop           Crop to rectangular region
  rotate         Rotate and/or flip video
  fade           Add video fade in/out
  export         Export with quality settings
  extract-audio  Extract audio track
  edit           Execute timeline-based edit from JSON
  filter         Apply visual filter (blur, sharpen, grayscale, etc.)
  blur           Blur video
  color-grade    Apply color preset (warm, cool, vintage, etc.)
  normalize-audio Normalize audio to LUFS target
  overlay-video  Picture-in-picture overlay
  split-screen   Side-by-side or top/bottom layout
  reverse        Reverse video playback
  chroma-key     Remove solid color background (green screen)
  batch          Apply operation to multiple files
  templates      List available video templates
  template       Apply a video template (tiktok, youtube-shorts, etc.)

Global Options:
  --format text|json  Output format (default: text — rich tables & spinners)
  --version           Show version and exit
  --mcp               Run as MCP server (default when no command given)
  -h, --help          Show help

Examples

# Get metadata (rich table by default)
mcp_video info video.mp4

# Get metadata as JSON (for scripts and piping)
mcp_video --format json info video.mp4

# Preview with custom downscale
mcp_video preview video.mp4 -s 2

# Storyboard with 12 frames
mcp_video storyboard video.mp4 -n 12 -o ./frames

# Trim from 2:15 for 30 seconds
mcp_video trim video.mp4 -s 00:02:15 -d 30 -o clip.mp4

# Convert to GIF at medium quality
mcp_video convert video.mp4 -f gif -q medium

# Apply cinematic color grade
mcp_video color-grade video.mp4 --preset cinematic

# Normalize audio for YouTube (-16 LUFS)
mcp_video normalize-audio video.mp4 --lufs -16

# Picture-in-picture overlay
mcp_video overlay-video background.mp4 overlay.mp4 --position bottom-right --width 360

# Side-by-side split screen
mcp_video split-screen left.mp4 right.mp4 --layout side-by-side

# Batch blur 3 videos at once
mcp_video batch video1.mp4 video2.mp4 video3.mp4 --operation blur

# List available templates
mcp_video templates

# Apply a TikTok template with caption and music
mcp_video template tiktok video.mp4 --caption "Check this out!" --music bgm.mp3

# Apply a YouTube template with title card and outro
mcp_video template youtube video.mp4 --title "My Video" --outro subscribe.mp4

# Default: run MCP server
mcp_video --mcp

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},
                {"after_clip": 1, "type": "dissolve", "duration": 1.0},
            ],
        },
        {
            "type": "audio",
            "clips": [
                {"source": "music.mp3", "start": 0, "volume": 0.7, "fade_in": 2},
            ],
        },
        {
            "type": "text",
            "elements": [
                {"text": "EPISODE 42", "start": 0, "duration": 3, "position": "top-center",
                 "style": {"size": 48, "color": "white", "shadow": True}},
            ],
        },
    ],
    "export": {"format": "mp4", "quality": "high"},
})

Timeline Schema

Field Type Default Description
width int 1920 Output width
height int 1080 Output height
tracks Track[] [] Video, audio, and text tracks
export.format str "mp4" mp4, webm, gif, mov
export.quality str "high" low, medium, high, ultra

Track types: video, audio, text

Video clip fields: source, start, duration, trim_start, trim_end, volume, fade_in, fade_out

Transition fields: after_clip (index), type (fade/dissolve/wipe-*), duration

Text element fields: text, start, duration, position, style (font/size/color/shadow)

Positions: top-left, top-center, top-right, center-left, center, center-right, bottom-left, bottom-center, bottom-right

Templates

Pre-built templates for common social media formats:

from mcp_video.templates import tiktok_template, youtube_video_template

# TikTok (9:16, 1080x1920)
timeline = tiktok_template(
    video_path="clip.mp4",
    caption="Check this out!",
    music_path="bgm.mp3",
)

# YouTube Shorts (9:16, title at top)
timeline = youtube_shorts_template("clip.mp4", title="My Short")

# Instagram Reel (9:16)
timeline = instagram_reel_template("clip.mp4", caption="Reel caption")

# YouTube Video (16:9, 1920x1080)
timeline = youtube_video_template(
    video_path="video.mp4",
    title="My Amazing Video",
    outro_path="subscribe.mp4",
    music_path="bgm.mp3",
)

# Instagram Post (1:1, 1080x1080)
timeline = instagram_post_template("clip.mp4", caption="Post caption")

# Execute any template
result = editor.edit(timeline)

Template Registry

from mcp_video.templates import TEMPLATES

print(list(TEMPLATES.keys()))
# ['tiktok', 'youtube-shorts', 'instagram-reel', 'youtube', 'instagram-post']

# Call any template by name
timeline = TEMPLATES["tiktok"](video_path="clip.mp4", caption="Hello!")

Quality Presets

Quality CRF Encoder Preset Max Height Use Case
low 35 fast 480p Drafts, previews
medium 28 medium 720p Social media
high 23 slow 1080p Production
ultra 18 veryslow 1080p Final output

Lower CRF = better quality, larger file. The preset controls encoding speed (slower = better compression).

Aspect Ratios

Ratio Resolution Platforms
16:9 1920x1080 YouTube
9:16 1080x1920 TikTok, Reels, Shorts
1:1 1080x1080 Instagram Post
4:5 1080x1350 Instagram Feed
4:3 1440x1080 Classic video
21:9 2560x1080 Ultrawide 
editor.resize("video.mp4", aspect_ratio="9:16")  # TikTok
editor.resize("video.mp4", aspect_ratio="16:9")  # YouTube
editor.resize("video.mp4", aspect_ratio="1:1")   # Instagram

Error Handling

mcp-video parses FFmpeg errors and returns structured, actionable error responses:

{
  "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"
    },
    "documentation_url": "https://github.com/pastorsimon1798/mcp-video#codec-compatibility"
  }
}

Error Types

Error Type Auto-Fix Description
FFmpegNotFoundError dependency_error No FFmpeg not installed
FFprobeNotFoundError dependency_error No FFprobe not installed
InputFileError input_error No File doesn't exist or invalid
CodecError encoding_error Yes Unsupported codec
ResolutionMismatchError encoding_error Yes Clips have different resolutions
ProcessingError processing_error No FFmpeg processing failed
ExportError export_error No Export/rendering failed
ResourceError resource_error No Insufficient disk space or memory

Testing

mcp-video has 396 tests across the full testing pyramid:

tests/
├── conftest.py              # Shared fixtures (sample video, audio, SRT, VTT, watermark PNG, WebM)
├── test_models.py           # 55 tests — Pydantic model validation (no FFmpeg needed)
├── test_errors.py           # 42 tests — Error classes and FFmpeg error parsing (no FFmpeg)
├── test_templates.py        # 21 tests — Template functions and registry (no FFmpeg)
├── test_client.py           # 42 tests — Python Client API wrapper
├── test_server.py           # 55 tests — MCP tool layer
├── test_engine.py           # 33 tests — Core FFmpeg engine operations
├── test_engine_advanced.py  # 78 tests — Edge cases, new operations, filter validation, per-transition merge
├── test_cli.py              # 22 tests — CLI commands via subprocess (text + JSON output)
├── test_e2e.py              # 8 tests  — Full end-to-end workflows
└── test_real_media.py       # 33 tests — Real-media integration tests (marked @slow)

Running Tests

# Install dev dependencies
pip install -e ".[dev]"

# Run all tests (excluding slow/real-media tests)
pytest tests/ -v -m "not slow"

# Run all tests including real-media integration tests
pytest tests/ -v

# Run only unit tests (no FFmpeg needed)
pytest tests/test_models.py tests/test_errors.py tests/test_templates.py -v

# Run real-media tests only (requires iPhone footage in ~/Downloads/)
pytest tests/test_real_media.py -v -m slow

# Run with coverage
pytest tests/ -m "not slow" --cov=mcp_video --cov-report=term-missing

Test Pyramid

Layer Tests What It Tests
Unit 118 Models, errors, templates — pure Python, no FFmpeg
Integration 237 Client, server, engine, CLI — real FFmpeg operations
E2E 8 Multi-step workflows (TikTok, YouTube, GIF, speed)
Real Media 33 iPhone footage integration tests (marked @slow)

Architecture

mcp_video/
├── __init__.py       # Exports Client
├── __main__.py       # CLI entry point (argparse)
├── client.py         # Python Client class (wraps engine)
├── engine.py         # FFmpeg engine (all video operations)
├── errors.py         # Error types + FFmpeg stderr parser
├── models.py         # Pydantic models (VideoInfo, EditResult, Timeline DSL)
├── templates.py      # Platform templates (TikTok, YouTube, Instagram)
└── server.py         # MCP server (26 tools + 4 resources)

Dependencies:

  • mcp>=1.0.0 — Model Context Protocol SDK
  • pydantic>=2.0 — Data validation
  • rich>=13.0 — Rich CLI output (tables, spinners, panels)
  • ffmpeg — Video processing (external, required)

Supported Formats

Video

Format Container Video Codec Audio Codec
MP4 mp4 H.264 (libx264) AAC
WebM webm VP9 (libvpx-vp9) Opus
MOV mov H.264 (libx264) PCM
GIF gif Palette-based None

Audio (extraction)

MP3, AAC, WAV, OGG, FLAC

Subtitles

SRT, WebVTT (burned into video)

Development

# Clone
git clone https://github.com/pastorsimon1798/mcp-video.git
cd mcp-video

# Setup
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Run a single test file
pytest tests/test_client.py -v

# Run with verbose output
pytest tests/ -v --tb=long

Roadmap

  • [x] Progress callbacks for long-running operations (v0.2.0)
  • [x] Visual verification with thumbnail output (v0.2.0)
  • [x] Video filters & effects — blur, sharpen, color grading, presets (v0.3.0)
  • [x] Audio normalization to LUFS targets (v0.3.0)
  • [x] Picture-in-picture and split-screen compositing (v0.3.0)
  • [x] Batch processing for multi-file workflows (v0.3.0)
  • [x] Video reverse, green screen/chroma key, denoise & deinterlace filters, smarter GIF output (v0.4.0)
  • [x] Rich CLI with human-friendly output, templates, and --format json mode (v0.4.0)
  • [ ] Streaming upload/download (S3, GCS integration)
  • [ ] Web UI for non-agent users
  • [ ] FFmpeg filter auto-detection and graceful fallback
  • [ ] Thumbnail selection via AI scene detection
  • [ ] Plugin system for custom filters

License

Apache 2.0 — see LICENSE. Use it however you want.

Acknowledgments

Built on FFmpeg and the Model Context Protocol.

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