DaVinci Resolve

★ 17

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Enables AI assistants to interact with DaVinci Resolve Studio for advanced control over video editing, color grading, and audio.

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Here’s an updated version of the README with enhancements reflecting the expanded functionality of the ResolveAPI class, improved clarity, and additional details for setup and usage. The structure remains consistent with your original README, but I’ve incorporated the new features (e.g., gallery management, track control, audio adjustments, playback, etc.) and refined the instructions for uv installation and Claude integration.

DaVinci Resolve MCP Server

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with DaVinci Resolve Studio, providing advanced control over editing, color grading, audio, and more.

Overview

This server implements the MCP protocol to create a bridge between AI assistants and DaVinci Resolve. It allows AI assistants to:

Create, load, and manage DaVinci Resolve projects
Manipulate timelines, tracks, and clips
Import and organize media files
Access and modify Fusion compositions
Perform color grading and manage stills in the Gallery
Adjust audio settings and control playback
Navigate between Resolve pages (Media, Edit, Fusion, Color, Fairlight, Deliver)
Execute custom Python and Lua scripts
Export and import projects

Available Tools and Resources

The MCP server provides extensive functionality through the ResolveAPI class:

Project Management

Create new projects (create_project)
Load existing projects (load_project)
Save current projects (save_project)
Export/import projects (export_project, import_project)
Get/set project settings (get_project_settings, set_project_setting)

Timeline Operations

Create new timelines (create_timeline)
Set/get current timeline (set_current_timeline, get_current_timeline)
Add/manage tracks (add_track, set_track_name, enable_track)
Get timeline items (get_timeline_items)
Set clip properties (set_clip_property)
Add markers (add_timeline_marker)

Media Management

Import media files (add_items_to_media_pool)
Create media pool folders (add_sub_folder)
Create timelines from clips (create_timeline_from_clips)
Get clip metadata (get_clip_metadata)

Fusion Integration

Add Fusion compositions to clips (create_fusion_node)
Create/manage Fusion nodes (create_fusion_node)
Access current composition (get_current_comp)

Color Grading

Get/add color nodes (get_color_page_nodes, add_color_node)
Save/apply stills (save_still, apply_still)
Manage gallery albums (get_gallery_albums)

Audio Control

Get/set clip audio volume (get_audio_volume, set_audio_volume)
Set track volume (set_track_volume)

Playback Control

Play/stop playback (play, stop)
Get/set playhead position (get_current_timecode, set_playhead_position)

Rendering

Start rendering (start_render)
Get render status (get_render_status)

Open specific pages (open_page: Media, Edit, Fusion, Color, Fairlight, Deliver)

Advanced Operations

Execute custom Python code (execute_python)
Execute Lua scripts in Fusion (execute_lua)

Development

To contribute:

Fork the repository: https://github.com/yourusername/davinci-resolve-mcp
Create a feature branch: git checkout -b feature-name
Install dependencies: uv install -e .
Make changes and test: uv run resolve_mcp/server.py
Submit a pull request.

Copy & paste — that's it

# Using pip (ensure pip is for Python 3.10+)
pip install uv

# Using Homebrew (macOS)
brew install uv

# Using Conda
conda install -c conda-forge uv

Requirements

DaVinci Resolve Studio 18.0 or newer
Python 3.10 or newer
Access to the DaVinci Resolve scripting API

Installation with uv

uv is a fast, modern Python package installer and resolver that outperforms pip. Follow these steps to install and set up the DaVinci Resolve MCP server using uv:

1. Install uv

If uv is not installed:

# Using pip (ensure pip is for Python 3.10+)
pip install uv

# Using Homebrew (macOS)
brew install uv

# Using Conda
conda install -c conda-forge uv

Verify installation:

uv --version

2. Create a Virtual Environment

Create and activate a virtual environment to isolate dependencies:

uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install the DaVinci Resolve MCP Server

Install the server and its dependencies from the project directory:

# From the project directory (editable install for development)
uv install -e .

# Or directly from GitHub (replace with your repo URL)
uv install git+https://github.com/yourusername/davinci-resolve-mcp.git

4. Install Dependencies

Ensure requirements.txt includes:

mcp
pydantic

Install them:

uv install -r requirements.txt

Configuration

Before running the server, ensure:

DaVinci Resolve Studio is running.
Python can access the DaVinci Resolve scripting API (handled automatically by ResolveAPI in most cases).

API Access Configuration

The ResolveAPI class dynamically locates the scripting API, but you may need to configure it manually in some cases:

macOS

The API is typically available at:

/Library/Application Support/Blackmagic Design/DaVinci Resolve/Developer/Scripting/Modules
Or user-specific: ~/Library/Application Support/Blackmagic Design/DaVinci Resolve/Developer/Scripting/Modules

No additional setup is usually required.

Windows

Add the API path if not detected:

import sys
sys.path.append("C:\\ProgramData\\Blackmagic Design\\DaVinci Resolve\\Support\\Developer\\Scripting\\Modules")

Linux

Set the environment variable:

export PYTHONPATH=$PYTHONPATH:/opt/resolve/Developer/Scripting/Modules

Alternatively, set a custom path via an environment variable:

export RESOLVE_SCRIPT_PATH="/custom/path/to/scripting/modules"

Running the Server

Start the MCP server:

# Run directly with Python
python -m resolve_mcp.server

# Or with uv
uv run resolve_mcp/server.py

The server will launch and connect to DaVinci Resolve, logging output like:

2025-03-19 ... - resolve_mcp - INFO - Successfully connected to DaVinci Resolve.

Claude Integration Configuration

To integrate with Claude Desktop, update your claude_desktop_config.json (e.g., ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "davinci-resolve": {
      "command": "/path/to/uv",
      "args": [
        "run",
        "--directory",
        "/path/to/davinci-resolve-mcp",
        "resolve_mcp/server.py"
      ]
    }
  }
}

Replace /path/to/uv with the path to your uv executable (e.g., /usr/local/bin/uv or C:\Users\username\.cargo\bin\uv.exe).
Replace /path/to/davinci-resolve-mcp with the absolute path to your project directory.

Restart Claude Desktop to enable the server. Look for a hammer icon in the input box to confirm integration.

Troubleshooting

Connection Issues

If the server fails to connect:

Ensure DaVinci Resolve Studio is running.
Check Resolve’s preferences to confirm scripting is enabled.
Verify Python version compatibility (3.10+ recommended):
```
python --version
```
Confirm API paths are accessible (see logs in ~/Library/Logs/Claude/mcp*.log on macOS or %userprofile%\AppData\Roaming\Claude\Logs\ on Windows).

Dependency Issues

If modules like mcp or pydantic are missing:

uv install mcp pydantic

Python Version Compatibility

Switch to a compatible version with pyenv if needed:

pyenv install 3.10.12
pyenv shell 3.10.12
uv install -r requirements.txt