Video editing
for AI agents and humans.

AI agents can write code, analyze documents, browse the web, create images — but video editing? Existing tools are either GUI-only (agents can't click buttons), raw FFmpeg wrappers (agents can't memorize hundreds of flags), or cloud APIs (expensive, slow, vendor lock-in). mcp-video bridges this gap.

Machine learning features for intelligent video processing.

Professional transitions for seamless clip connections.

Generate sound effects from code without external audio files.

"Can't I just have Claude Code run ffmpeg commands?" Sure — if you enjoy debugging 200-character filter graphs, wrestling with flag order semantics, and paying dollars per short clip on cloud APIs. Here's why mcp-video is different.

Every tool returns structured JSON. On success, you get output paths, duration, resolution. On failure, you get error types with auto-fix suggestions.

mcp-video works as an MCP server for AI agents, a Python library for scripts, and a rich CLI tool for the terminal with human-friendly output and templates.

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

from mcp_video import Client

editor = Client()
clip = editor.trim("v.mp4", start="0:30", duration="15")
final = editor.resize(clip.output_path, aspect_ratio="9:16")
result = editor.export(final.output_path)
print(result.resolution)  # 1080x1920

# Rich table output (default)
$ mcp-video info video.mp4
# ┌─────────────┬──────────────────┐
# │ Property    │ Value            │
# ├─────────────┼──────────────────┤
# │ Duration    │ 45.23s           │
# │ Resolution  │ 1920x1080        │
# │ FPS         │ 30               │
# └─────────────┴──────────────────┘

# JSON output for scripts
$ mcp-video --format json info video.mp4

# Trim with progress spinner
$ mcp-video trim video.mp4 -s 0:30 -d 15

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

# List all templates
$ mcp-video templates

Describe multi-track edits with video clips, audio, text overlays, transitions, and export settings — all in one call.

editor.edit({
    "width": 1080, "height": 1920,
    "tracks": [
        {
            "type": "video",
            "clips": [
                {"source": "intro.mp4", "duration": 5},
                {"source": "main.mp4", "trim_start": 10, "duration": 30},
            ],
            "transitions": [{"after_clip": 0, "type": "fade", "duration": 1.0}],
        },
        {
            "type": "audio",
            "clips": [{"source": "music.mp3", "volume": 0.7}],
        },
        {
            "type": "text",
            "elements": [{"text": "EPISODE 42", "position": "top-center"}],
        },
    ],
    "export": {"format": "mp4", "quality": "high"},
})

Pre-built templates handle the correct dimensions, text positioning, and export settings for each social media platform.

Core video paths use actual FFmpeg operations, while dependency-heavy AI and Remotion paths are isolated with targeted mocks. The non-slow suite currently passes with 733 tests.