Omni-Video Studio MCP

The Omni-Video Studio MCP is an enterprise-grade, autonomous Model Context Protocol (MCP) server that empowers any LLM-enabled IDE (Cursor, Claude Code, Antigravity) to act as a professional video editor.

It evolves simple transcription-based editing into a deterministic, token-efficient, and pipeline-driven workflow, featuring agent-native motion graphics (Hyperframes), visual metadata proxies, and high-fidelity final renders.

🌟 Key Features

1. Metadata Proxy Ingestion: Instead of streaming expensive video tokens to an LLM, this server pre-processes footage to extract a takes_packed.md (audio mapping) and a Visual Scene Graph. The agent edits using text proxies, cutting costs and accelerating reasoning.
2. Hyperframes Engine: Forget complex Node.js dependencies (e.g., Remotion). The agent generates deterministic HTML/CSS motion graphics which are instantly rendered to transparent video using Playwright.
3. Advanced Rendering Pipeline: Powered by robust FFmpeg filter graphs, the final output supports EDL (Edit Decision List) cuts, overlay rendering, Subtitle burning, LUT color grading, and optional DeepFilterNet AI audio restoration.
4. IDE-Agnostic: Because it adheres to the official MCP specification, it drops directly into Cursor, Antigravity, or Claude Desktop without custom plugins.

📦 Installation

Prerequisites:

• python 3.10+
• ffmpeg (must be installed on your system path)
• uv (recommended for dependency management)

# Clone the repository
git clone https://github.com/Mallet-Builds/omni-video-mcp.git
cd omni-video-mcp

# Install dependencies
uv venv
source .venv/bin/activate
uv pip install -e .

# Install Playwright browsers (for Hyperframes)
playwright install chromium

🛠 Configuration

Add the server to your IDE's MCP settings file (e.g., ~/.gemini/antigravity/mcp_config.json, ~/.cursor/mcp.json, or Claude Desktop config):

{
  "mcpServers": {
    "omni-video-mcp": {
      "command": "uv",
      "args": [
        "run",
        "/path/to/omni-video-mcp/server.py"
      ],
      "env": {
        "ELEVENLABS_API_KEY": "your_api_key_here" 
      }
    }
  }
}

Note: The `ELEVENLABS_API_KEY` is currently required for high-fidelity word-level transcription mapping during ingestion.

🎬 How it Works (The Agent Pipeline)

When the agent uses this MCP server, it follows a 4-phase architecture:

1. Phase 1: Ingestion (`omni_video_ingest`)

The agent scans your raw .mp4 / .mov files, extracting a packed markdown transcript and an initial Visual Scene Graph.

1. Phase 2: Director's Cut (`omni_video_preview`)

The agent uses the transcript to construct an EDL (Edit Decision List) of the best takes. Ambiguous cuts can be visually verified by generating filmstrip PNGs via the preview tool.

1. Phase 3: VFX (`omni_video_generate_vfx`)

The agent generates HTML/CSS motion graphics (lower thirds, b-roll layouts) and the server renders them deterministically into transparent .webm videos via Hyperframes.

1. Phase 4: Sweetening & Render (`omni_video_render`)

The agent passes the EDL, VFX timestamps, and render settings to the server, which builds a complex FFmpeg graph to concatenate the footage, grade it, restore the audio, and export a final master.

🤝 Contributing

Contributions are welcome! If you're adding new render pipeline capabilities (like auto-tracking or local whisper fallbacks), please open a PR. Ensure that any added Python dependencies are added to the pyproject.toml using uv add <package>.

📄 License

MIT License