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Model Context Protocol server for DaVinci Resolve integration

Project description

DaVinci MCP Professional

A modern, professional implementation of a Model Context Protocol server for DaVinci Resolve integration. This project is a hard/project fork from the excellent work done by @samuelgursky at https://github.com/samuelgursky/davinci-resolve-mcp. It's an independent project now due to major overhaul and restructuring making it incompatible with the original repo. DaVinci MCP Professional is a fully enterprise-grade implementation of an MCP specifically designed to expose the full range of functionality of either DaVinci Resolve or DaVinci Resolve Studio to MCP clients. Supported clients include both Claude Desktop (preferred) or Cursor.

Installation Options

🚀 One-Click Installation (Recommended)

DaVinci MCP Professional is available as a Desktop Extension (DXT) for easy installation:

  1. Download the latest .dxt file from Releases
  2. Open Claude Desktop and go to Settings > Extensions
  3. Drag and drop the .dxt file to install
  4. Configure any optional settings (DaVinci Resolve path, debug mode)
  5. Start DaVinci Resolve and begin using AI-assisted video editing!

⚙️ Manual Installation

For developers and advanced users who prefer manual setup:

  1. Clone the repository
  2. Install dependencies: pip install -r requirements.txt
  3. Configure Claude Desktop: Add server configuration to claude_desktop_config.json
  4. See USING.md for detailed manual setup instructions

What Makes This Professional

This is a complete architectural rewrite and cleanup of existing DaVinci Resolve MCP implementations:

  • Clean Architecture: Proper separation of concerns between MCP protocol and DaVinci Resolve API
  • Modern Python: Uses current best practices with type hints, async/await, and comprehensive error handling
  • Simplified Setup: Single command installation with automatic dependency management
  • Windows Compatible: Proper encoding handling and console output for Windows environments
  • Standardized Dependencies: Uses uv for fast, reliable dependency management
  • Comprehensive Testing: Built-in test suite to verify functionality
  • Production Ready: Clean codebase suitable for professional environments

Architecture Highlights

This implementation emphasizes:

  • Reliability: Comprehensive error handling and graceful failure modes
  • Maintainability: Clean separation of concerns and modular design
  • Performance: Efficient async/await patterns and minimal overhead
  • Compatibility: Cross-platform support with Windows-specific optimizations
  • Professional Standards: Proper logging, testing, and documentation

Usage

See USING located elsewhere in this repo.

Getting Help

See BUGS located elsewhere in this repo.

License

See COPYING located elsewhere in this repo.

Contributing

See CONTRIBUTING located elsewhere in this repo.

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