DaVinci Resolve MCP Server
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Alternatives to DaVinci Resolve MCP Server
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Related Servers
- AlicenseAqualityAmaintenanceA professional implementation of a Model Context Protocol server that enables integration between DaVinci Resolve video editing software and AI assistants like Claude Desktop or Cursor.14625GPL 3.0
- AlicenseNot gradedqualityDmaintenanceA Model Context Protocol (MCP) server that connects AI coding assistants to DaVinci Resolve, enabling query and control through natural language.MIT
- AlicenseAqualityDmaintenanceAllows AI assistants like Claude to directly interact with and control DaVinci Resolve through the Model Context Protocol, providing capabilities for project management, timeline manipulation, media management, and Fusion integration.1478MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that exposes the complete DaVinci Resolve scripting API, enabling AI assistants to control DaVinci Resolve programmatically with over 440 tools for project management, timeline editing, color grading, rendering, and more.13MIT
- FlicenseAqualityBmaintenanceAn MCP server that gives Claude Code hands inside DaVinci Resolve Studio, enabling project management, status checks, snapshots, and arbitrary Python scripting via the Resolve API.51-
- AlicenseBqualityDmaintenanceConnects DaVinci Resolve Studio to Claude AI via the Model Context Protocol, enabling natural language control over video editing, color grading, Fusion compositing, AI features, and more.53379MIT
TDQS
Scored across 32 tools
Most tools target a distinct resource/action pair, and descriptions clarify contexts like color vs Fusion nodes. The many set_ and add_ variants could occasionally be confused, but boundaries are mostly clear.
All tools use lowercase snake_case with a verb-first pattern like create_, set_, add_, and import_. Even one-off actions like refresh and play_timeline fit the overall predictable style.
32 tools is above the ideal range, but the broad scope of DaVinci Resolve—projects, timelines, media, color, Fusion, playback, and render—justifies most of them. The set feels heavy, but not bloated with duplicates.
The toolset is heavily write/set-oriented with no list/get/delete operations for projects, timelines, tracks, or clips, making it hard for agents to inspect state. execute_lua can work around this, but the structured surface has significant lifecycle gaps.