DaVinci Resolve Local Bridge MCP server

Davinc-Resolve-Local-Bridge-MCP

<!-- mcp-name: io.github.Airta-Admin/davinc-resolve-local-bridge-mcp -->

Control DaVinci Resolve from any AI assistant — Claude, Cursor, Devin, and more.

218 tools. Resolve API and optional-extension coverage. Works with DaVinci Resolve Free and Studio.

What Is This?

Davinc-Resolve-Local-Bridge-MCP is a Model Context Protocol (MCP) server that gives AI assistants controlled access to DaVinci Resolve. It exposes 218 tools covering projects, timelines, media, Fusion, color grading, rendering, and supported optional extensions.

How It Works

Your AI Assistant (Claude, Cursor, Devin, etc.)
       │
       │  talks MCP (stdio)
       ▼
  mcp_server/server.py        ← runs on your machine
       │
       │  talks HTTP (localhost:8787)
       ▼
  DaVinciResolveBridge.py ← runs INSIDE DaVinci Resolve
       │                        (started from the Workflow Integration)
       ▼
  DaVinci Resolve API         ← full read + write access

The bridge script runs inside DaVinci Resolve's process, giving it full access to the Resolve scripting API — even on the Free edition (which blocks external scripting). The MCP server runs as a separate process and proxies tool calls to the bridge over localhost HTTP.

Quick Start

Prerequisites

• DaVinci Resolve 18.5+ (Free or Studio)
• Python 3.10+ on your machine
• An MCP-compatible AI assistant (Claude Desktop, Cursor, Devin, etc.)

Step 1 — Install the Workflow Integration and Bridge

Run the installer:

python install.py

The installer adds the user-facing launcher under Workspace → Workflow Integrations and installs the underlying bridge script. Restart Resolve once after installation so it discovers the integration.

For a manual installation, copy workflow/DaVinci Resolve Local Bridge MCP Server Connection.py and the workflow/assets directory to Resolve's Workflow Integration Plugins directory. Also copy bridge/Bridge-Connection-Script.py to Resolve's scripts folder as DaVinciResolveBridge.py. The Scripts entry is retained as a fallback, not the normal launch path.

Step 2 — Install MCP Server Dependencies

pip install -r requirements.txt

Step 3 — Configure Your AI Assistant

Add the MCP server to your assistant's configuration file. The server path is mcp_server/server.py in this repo.

Claude Desktop

Edit claudedesktopconfig.json:

{
  "mcpServers": {
    "davinci-resolve-local-bridge": {
      "command": "python",
      "args": ["C:/path/to/Davinc-Resolve-Local-Bridge-MCP/mcp_server/server.py"]
    }
  }
}

Cursor

Edit .cursor/mcp.json:

{
  "mcpServers": {
    "davinci-resolve-local-bridge": {
      "command": "python",
      "args": ["C:/path/to/Davinc-Resolve-Local-Bridge-MCP/mcp_server/server.py"]
    }
  }
}

Devin

Edit mcp_config.json:

{
  "mcpServers": {
    "resolve-local-bridge": {
      "command": "python",
      "args": ["C:/path/to/Davinc-Resolve-Local-Bridge-MCP/mcp_server/server.py"]
    }
  }
}

Claude Code

claude mcp add davinci-resolve-local-bridge -- python C:/path/to/Davinc-Resolve-Local-Bridge-MCP/mcp_server/server.py

Any MCP Client (generic)

The server uses stdio transport. Launch it with:

Shortened. The full README is on GitHub.