davinci resolve mcp
A server that enables LLM applications to interact directly with DaVinci Resolve video editing software, allowing AI-assisted capabilities like accessing timeline information and automating editing workflows.
A server that enables LLM applications to interact directly with DaVinci Resolve video editing software, allowing AI-assisted capabilities like accessing timeline information and automating editing workflows.
A Model Context Protocol (MCP) server that connects AI coding assistants (Cursor, Claude Desktop) to DaVinci Resolve, enabling them to query and control DaVinci Resolve through natural language.
For a comprehensive list of implemented and planned features, see docs/FEATURES.md.
For detailed installation instructions, please see INSTALL.md. This guide covers: - Prerequisites and system requirements - Step-by-step installation process - Configuration details - Common troubleshooting steps
Platform | Status | One-Step Install | Quick Start |
---|---|---|---|
macOS | ✅ Stable | ./install.sh |
./run-now.sh |
Windows | ✅ Stable | install.bat |
run-now.bat |
Linux | ❌ Not supported | N/A | N/A |
The easiest way to get started is with our new unified installation script. This script does everything automatically:
Clone the repository:
git clone https://github.com/samuelgursky/davinci-resolve-mcp.git
cd davinci-resolve-mcp
Make sure DaVinci Resolve Studio is installed and running
Run the installation script: macOS/Linux:
./install.sh
Windows:
install.bat
This will: 1. Automatically detect the correct paths on your system 2. Create a Python virtual environment 3. Install the MCP SDK from the official repository 4. Set up environment variables 5. Configure Cursor/Claude integration 6. Verify the installation is correct 7. Optionally start the MCP server
You can also use the original quick start scripts:
Windows Users:
run-now.bat
macOS Users:
chmod +x run-now.sh
./run-now.sh
For configuration of DaVinci Resolve MCP with different AI assistant clients like Cursor or Claude, see the config-templates directory.
For detailed troubleshooting guidance, refer to the INSTALL.md file which contains solutions to common issues.
run-now.sh
looking for files in the wrong locationsscripts/cursor_resolve_server.log
for troubleshootingFor issues and feature requests, please use the GitHub issue tracker.
After installation, you have several ways to start the server:
The repository includes dedicated scripts for launching with specific clients:
# For Cursor integration (macOS)
chmod +x scripts/mcp_resolve-cursor_start
./scripts/mcp_resolve-cursor_start
# For Claude Desktop integration (macOS)
chmod +x scripts/mcp_resolve-claude_start
./scripts/mcp_resolve-claude_start
These specialized scripts: - Set up the proper environment for each client - Verify DaVinci Resolve is running - Configure client-specific settings - Start the MCP server with appropriate parameters
Before connecting AI assistants, verify your environment is properly configured:
# On macOS
./scripts/check-resolve-ready.sh
# On Windows
./scripts/check-resolve-ready.bat
These scripts will: - Verify DaVinci Resolve is running (and offer to start it) - Check environment variables are properly set - Ensure the Python environment is configured correctly - Validate Cursor/Claude configuration - Optionally launch Cursor
For advanced users, our unified launcher provides full control over both Cursor and Claude Desktop servers:
# Make the script executable (macOS only)
chmod +x scripts/mcp_resolve_launcher.sh
# Run in interactive mode
./scripts/mcp_resolve_launcher.sh
# Or use command line options
./scripts/mcp_resolve_launcher.sh --start-cursor # Start Cursor server (uses mcp_resolve-cursor_start)
./scripts/mcp_resolve_launcher.sh --start-claude # Start Claude Desktop server (uses mcp_resolve-claude_start)
./scripts/mcp_resolve_launcher.sh --start-both # Start both servers
./scripts/mcp_resolve_launcher.sh --stop-all # Stop all running servers
./scripts/mcp_resolve_launcher.sh --status # Show server status
Additional options:
- Force mode (skip Resolve running check): --force
- Project selection: --project "Project Name"
For a complete manual installation:
Clone this repository:
git clone https://github.com/samuelgursky/davinci-resolve-mcp.git
cd davinci-resolve-mcp
Create a Python virtual environment:
# Create virtual environment
python -m venv venv
# Activate it
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venvScriptsactivate
# Install dependencies from requirements.txt
pip install -r requirements.txt
# Alternatively, install MCP SDK directly
pip install git+https://github.com/modelcontextprotocol/python-sdk.git
Set up DaVinci Resolve scripting environment variables:
For macOS:
export RESOLVE_SCRIPT_API="/Library/Application Support/Blackmagic Design/DaVinci Resolve/Developer/Scripting"
export RESOLVE_SCRIPT_LIB="/Applications/DaVinci Resolve/DaVinci Resolve.app/Contents/Libraries/Fusion/fusionscript.so"
export PYTHONPATH="$PYTHONPATH:$RESOLVE_SCRIPT_API/Modules/"
For Windows:
set RESOLVE_SCRIPT_API=C:ProgramDataBlackmagic DesignDaVinci ResolveSupportDeveloperScripting
set RESOLVE_SCRIPT_LIB=C:Program FilesBlackmagic DesignDaVinci Resolvefusionscript.dll
set PYTHONPATH=%PYTHONPATH%;%RESOLVE_SCRIPT_API%Modules
Alternatively, run the pre-launch check script which will set these for you:
# On macOS
./scripts/check-resolve-ready.sh
# On Windows
./scripts/check-resolve-ready.bat
For macOS (~/.cursor/mcp.json
):
{
"mcpServers": {
"davinci-resolve": {
"name": "DaVinci Resolve MCP",
"command": "/path/to/your/venv/bin/python",
"args": [
"/path/to/your/davinci-resolve-mcp/src/main.py"
]
}
}
}
For Windows (%APPDATA%Cursormcp.json
):
{
"mcpServers": {
"davinci-resolve": {
"name": "DaVinci Resolve MCP",
"command": "C:pathtovenvScriptspython.exe",
"args": ["C:pathtodavinci-resolve-mcpsrcmain.py"]
}
}
}
# For Cursor
./scripts/mcp_resolve-cursor_start
# For Claude Desktop
./scripts/mcp_resolve-claude_start
Start the Cursor server using the dedicated script:
./scripts/mcp_resolve-cursor_start
Or use the universal launcher:
./scripts/mcp_resolve_launcher.sh --start-cursor
Start Cursor and open a project.
In Cursor's AI chat, you can now interact with DaVinci Resolve. Try commands like:
Create a claude_desktop_config.json
file in your Claude Desktop configuration directory using the template in the config-templates
directory.
Run the Claude Desktop server using the dedicated script:
./scripts/mcp_resolve-claude_start
Or use the universal launcher:
./scripts/mcp_resolve_launcher.sh --start-claude
In Claude Desktop, you can now interact with DaVinci Resolve using the same commands as with Cursor.
Windows support is stable in v1.3.3 and should not require additional troubleshooting:
- Ensure DaVinci Resolve is installed in the default location
- Environment variables are properly set as described above
- Windows paths may require adjustment based on your installation
- For issues, please check the logs in the logs/
directory
Make sure DaVinci Resolve is running before starting the server. If the server can't connect to Resolve, check that:
davinci-resolve-mcp/
├── README.md # This file
├── docs/ # Documentation
│ ├── FEATURES.md # Feature list and status
│ ├── CHANGELOG.md # Version history
│ ├── VERSION.md # Version information
│ ├── TOOLS_README.md # Tools documentation
│ ├── PROJECT_MCP_SETUP.md # Project setup guide
│ └── COMMIT_MESSAGE.txt # Latest commit information
├── config-templates/ # Configuration templates
│ ├── sample_config.json # Example configuration
│ ├── cursor-mcp-example.json # Cursor config example
│ └── mcp-project-template.json # MCP project template
├── scripts/ # Utility scripts
│ ├── tests/ # Test scripts
│ │ ├── benchmark_server.py # Performance tests
│ │ ├── test_improvements.py # Test scripts
│ │ ├── test_custom_timeline.py # Timeline tests
│ │ ├── create_test_timeline.py # Create test timeline
│ │ ├── test-after-restart.sh # Test after restart (Unix)
│ │ └── test-after-restart.bat # Test after restart (Windows)
│ ├── batch_automation.py # Batch automation script
│ ├── restart-server.sh # Server restart script (Unix)
│ ├── restart-server.bat # Server restart script (Windows)
│ ├── run-now.sh # Quick start script (Unix)
│ └── run-now.bat # Quick start script (Windows)
├── resolve_mcp_server.py # Main server implementation
├── src/ # Source code
│ ├── api/ # API implementation
│ ├── features/ # Feature modules
│ └── utils/ # Utility functions
├── logs/ # Log files
├── tools/ # Development tools
├── assets/ # Project assets
└── examples/ # Example code
MIT
Samuel Gursky ([email protected]) - GitHub: github.com/samuelgursky
If you'd like to contribute, please check the feature checklist in the repo and pick an unimplemented feature to work on. The code is structured with clear sections for different areas of functionality.
MIT
After cleanup, the project has the following structure:
resolve_mcp_server.py
- The main MCP server implementationrun-now.sh
- Quick start script that handles setup and runs the serversetup.sh
- Complete setup script for installationcheck-resolve-ready.sh
- Pre-launch check to verify DaVinci Resolve is readystart-server.sh
- Script to start the serverrun-server.sh
- Simplified script to run the server directlyKey Directories:
- src/
- Source code and modules
- assets/
- Project assets and resources
- logs/
- Log files directory
- scripts/
- Helper scripts
When developing, it's recommended to use ./run-now.sh
which sets up the environment and launches the server in one step.
See docs/CHANGELOG.md for a detailed history of changes.
When integrating with Cursor, follow these specific steps:
Make sure DaVinci Resolve is running before starting Cursor
Install required dependencies:
# From the davinci-resolve-mcp directory:
pip install -r requirements.txt
Note: This will install the MCP package and other dependencies automatically.
Set up the MCP server configuration in Cursor:
Create or edit ~/.cursor/mcp.json
on macOS (or %USERPROFILE%.cursormcp.json
on Windows):
{
"mcpServers": {
"davinci-resolve": {
"name": "DaVinci Resolve MCP",
"command": "/path/to/your/venv/bin/python",
"args": [
"/path/to/your/davinci-resolve-mcp/src/main.py"
]
}
}
}
Important Notes:
- Use main.py
as the entry point (not resolve_mcp_server.py
)
- Use absolute paths in the configuration