MCP Connector

Control DaVinci Resolve with AI

MCP server that connects AI assistants to DaVinci Resolve Studio's scripting API, enabling automated editing, grading, Fusion compositing, and render control

Works with githubcursorclaude desktop

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91
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out of 100
Updated last month
Version 2.57.5
Models
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Why it matters

Integrate AI programming assistants like Cursor and Claude Desktop with DaVinci Resolve. Control video editing software using natural language commands for enhanced productivity.

Outcomes

What it gets done

01

Connect AI assistants to DaVinci Resolve via an MCP server.

02

Control DaVinci Resolve features using natural language prompts.

03

Automate tasks such as project and timeline management.

04

Get DaVinci Resolve version and project details.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-davinci-resolve | bash

Capabilities

Tools your agent gets

get_davinci_resolve_version

Get the version of DaVinci Resolve currently running

get_current_page

Get the current page in DaVinci Resolve (Edit, Color, Fusion, etc.)

switch_page

Switch to a different page in DaVinci Resolve

list_projects

List all available projects in DaVinci Resolve

get_current_project

Get the name of the current project

open_project

Open a project by name in DaVinci Resolve

create_project

Create a new project in DaVinci Resolve

save_project

Save the current project in DaVinci Resolve

+4 tools

Overview

DaVinci Resolve MCP Server

MCP server providing AI assistant control of DaVinci Resolve Studio through the official Scripting API, with compound and granular tool modes, source-safe media analysis, and a local browser control panel. Use when you need AI assistants to automate DaVinci Resolve workflows including project management, timeline editing, media pool organization, color grading, Fusion compositing, Fairlight audio, render delivery, or extension authoring-all while preserving source media integrity.

What it does

Big Job: Automate DaVinci Resolve Studio workflows-from project setup and timeline editing to color grading, Fusion compositing, and render delivery-by letting AI assistants control Resolve through natural language commands.

Small Job: Execute specific Resolve operations like creating timelines from media pool clips, detecting sync events in footage, publishing analysis metadata, probing timelines for gaps, building render plans, copying grades, or installing custom extensions-all through MCP tools that wrap the official Resolve API.

Getting Started:

npx davinci-resolve-mcp setup

Before connecting, open DaVinci Resolve Studio and set Preferences > General > External scripting using to Local. The installer detects Resolve paths, creates a virtual environment, and configures Claude Desktop, VS Code, Cursor, Windsurf, Zed, Continue, Cline, and other MCP clients.

Example Commands:

"List all projects and open the one called 'My Film'"
"Create a timeline called 'Assembly Cut' from all clips in the current bin"
"Build a multicam prep timeline from selected camera angles and preserve source media"
"Detect 2-pops or slate claps and suggest record offsets for sync prep"
"Probe this timeline for gaps, overlaps, missing media, and source frame ranges"
"Build a ProRes 422 HQ render plan, validate the settings, and queue the job"
"Snapshot this clip's grade, validate a CDL update, and export a temp LUT"

The server offers two modes: Compound (default) groups related Resolve operations behind action parameters to keep context usage low; Full exposes one MCP tool per Resolve API method. A local browser control panel ships for inspecting Resolve state, running source-safe media analysis, and editing analysis output. The server treats camera originals as immutable-analysis reads source files and writes reports only to sidecar directories, with metadata publishing confined to Resolve's project database.

Source README

DaVinci Resolve MCP Server

Version
npm
API Coverage
Tools
Tested
DaVinci Resolve
Python
License

A Model Context Protocol (MCP) server that lets AI assistants control DaVinci Resolve Studio through the official Scripting API. It provides full API coverage plus guarded workflow helpers for editing, media pool organization, render setup, review markers, grading, Fusion, Fairlight, project lifecycle tasks, extension authoring, and source-safe media analysis.

A local browser control panel ships with the server for inspecting Resolve state, running source-safe analysis, drilling into analyzed clips and shots, and editing analysis output inline. See the Control Panel Guide for the full tour.

Quick Start

npx davinci-resolve-mcp setup

Before connecting, open DaVinci Resolve Studio and set Preferences > General > External scripting using to Local. The npm launcher installs a managed copy under your user application-data directory, then runs the universal Python installer. The installer creates a virtual environment, detects Resolve paths, and can configure Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Zed, Continue, Cline, Roo Code, OpenCode, and JetBrains IDEs.

For source installs:

git clone https://github.com/samuelgursky/davinci-resolve-mcp.git
cd davinci-resolve-mcp
python install.py

For platform paths, client-specific config, and manual setup, see Installation and Configuration.

The installer and server check the latest GitHub release for MCP updates. Checks are best-effort and throttled; the server never blocks MCP startup for a prompt. The installer can prompt, snooze, ignore a release, disable checks, or apply an opt-in safe auto-update for clean git checkouts.

Local Control Panel

Launch the single-user local control panel from the repository root:

venv/bin/python -m src.control_panel

The command starts a localhost server and opens the control panel in your browser. To have an AI coding agent do this, ask: "Open the Resolve MCP control panel for this repo." Agents should use venv/bin/python -m src.control_panel unless your Python environment is already active. Persisted analysis jobs refresh the local search index automatically after successful slices; the manual Build Index action is for rebuilding from existing reports.

Server Modes

Mode Entry point Tools Best for
Compound src/server.py 34 Default mode for most assistants. Related Resolve operations are grouped behind action parameters to keep context usage low.
Full / granular src/server.py --full or src/resolve_mcp_server.py 341 Power users who want one MCP tool per Resolve API method.

The compound server is recommended unless you specifically need the granular one-tool-per-method surface.

What You Can Do

"List all projects and open the one called 'My Film'"
"Create a timeline called 'Assembly Cut' from all clips in the current bin"
"Build a multicam prep timeline from selected camera angles and preserve source media"
"Detect 2-pops or slate claps and suggest record offsets for sync prep"
"Publish analysis summaries, keywords, people, and slate hints into Resolve clip metadata"
"Probe this timeline for gaps, overlaps, missing media, and source frame ranges"
"Safely import this image sequence, organize it into bins, and normalize clip metadata"
"Build a ProRes 422 HQ render plan, validate the settings, and queue the job"
"Copy review markers from the timeline to the selected clip and export a review report"
"Snapshot this clip's grade, validate a CDL update, and export a temp LUT"
"Create a Fusion TextPlus overlay on the selected clip and verify graph connections"
"Report audio channel mappings, voice isolation availability, and subtitle support"
"Install this MCP-marked DCTL or script, classify refresh/restart needs, then remove it"

Core Capabilities

Area What the compound server supports
App and project control Launch/reconnect, page switching, project CRUD, project folders, databases, cloud project wrappers, settings, presets, archives
Media pool and ingest Safe import, image sequences, multicam prep timelines, bin organization, metadata normalization, metadata field inventory, marks, annotations, relink/proxy/full-resolution guards
Media analysis Source-safe file/clip/bin/project analysis, 2-pop/slate-clap sync-event detection, default Resolve metadata and Media Pool marker writeback, persisted analysis artifacts, existing-report reuse, host_chat_paths visual analysis (finalized per clip with commit_vision, works with any vision-capable MCP client) with opt-out, transcription with opt-out
Timeline editing and conform Track/item probing, title text key scans/writes, copy/move/duplicate helpers, range operations, gaps/overlaps, source ranges, checked interchange exports/imports
Review annotations Timeline/item/clip markers, custom data, flags, clip color, copy/move/sync cleanup, review reports, marker thumbnail review
Color and grading Node graph probing, CDL validation, grade copy, DRX/LUT helpers, versions, Gallery stills, color groups
Fusion Timeline-item comps, safe tool creation, input writes, port inspection, validated connections, scoped bulk writes
Audio and Fairlight Track/item probes, source mapping, guarded audio property writes, voice isolation, auto-sync planning, transcription/subtitle probes
Render and deliver Format/codec matrix probing, render settings validation, queued job lifecycle checks, guarded Quick Export
Extension authoring Fuse, DCTL, ACES DCTL, and Resolve-page Lua/Python script lifecycle helpers with safe MCP-marked install/remove

Source Media Safety

This project treats camera originals and source media as immutable. Analysis tools read source files and write reports only to sidecar, scratch, or project analysis directories; confirmed metadata publishing writes only to Resolve's project database. The server must not modify, transcode, proxy, or create derivatives of source media unless the user explicitly asks for that. See Media Analysis Guide for the detailed source-safe workflow.

Security Posture

The default server is a local stdio process launched by your MCP client; it does not expose a network listener or built-in multi-user auth surface. Tool metadata includes MCP client-safety hints for read-only, destructive, idempotent, and external-resource operations. See Security Policy for operational boundaries, confirmation guidance, and vulnerability reporting.

Key Stats

Metric Value
MCP Tools 32 compound / 341 granular
Kernel Actions 136 guarded workflow actions across 9 compound tools
API Methods Covered 336/336 (100%)
Methods Live Tested 331/336 (98.5%)
Live Test Pass Rate 331/331 (100%)
Tested Against DaVinci Resolve 19.1.3 Studio + Resolve 20.3.2 Studio

For method-by-method status, see API Coverage and Test Results. For current workflow support, see Kernel Action Coverage.

analyze_media executes directly by default, persists inspectable reports/artifacts under the analysis root, requests host-chat visual analysis via the host_chat_paths protocol (analyze returns absolute frame paths + a JSON schema; the host chat reads each frame as an image and calls media_analysis(action="commit_vision", ...) to finalize), runs transcription through the configured local backend, and writes analysis summaries plus source-time Media Pool clip markers back to the Resolve project. Pass include_visuals=false, include_transcription=false, publish_metadata=false, timed_markers=no, or dry_run=true only when you want to opt out of those default behaviors. Skipping commit_vision leaves the run in pending_host_vision_analysis - surfaced as a failure mode, not silently downgraded.

Documentation

Document Use it for
Installation and Configuration Requirements, installer options, supported clients, server modes, manual config
API Coverage and Test Results Key stats, API coverage table, live-test status, full method reference
Kernel Action Coverage Current guarded workflow action map
AI Skill Reference Operational context for AI assistants using the compound server
Control Panel Guide Local browser panel tour: Overview, Review (bin/clip/shot), Analyze, Setup, Preferences
Media Analysis Guide Source-safe FFprobe, FFmpeg, Whisper, sidecar, and analysis-root workflows
Multicam Setup Helper Guide Stacked timeline prep, helper/API boundary, and Resolve UI conversion steps
Editorial Decision Guide Project-owned editorial craft guidance for analysis and timeline decisions
Color Decision Guide Project-owned color correction guidance and Resolve color API boundaries
Contributing and Project Layout Contribution workflow, platform support, security notes, repository structure
Security Policy Local stdio trust boundary, tool metadata, confirmation guidance, reporting
Release Process Maintainer release checklist, version surfaces, validation, tags, and release notes
Changelog Historical release notes

Extension authoring references live in docs/authoring. Resolve developer-package notes live in docs/notes and docs/integrations. Prompt recipes live in examples.

Requirements

  • DaVinci Resolve Studio 18.5+ on macOS, Windows, or Linux. The free edition does not support external scripting.
  • Python 3.10+ (3.10-3.12 is the lowest-risk range). Python 3.13/3.14 also work on recent Resolve builds (verified on Studio 20.3.2); older builds may fail to connect on 3.13+, in which case use 3.10-3.12.
  • Resolve external scripting set to Local.

Resolve 19.1.3 remains the compatibility baseline. Resolve 20.x scripting calls are additive, version-guarded, and live-tested on 20.3.2. Resolve 21.0 scripting additions (audio classification, speaker-detection transcription, IntelliSearch, slate analysis, motion-deblur, speech generation, session background-task control) are exposed behind runtime capability detection, so they stay inert on older builds and activate automatically on Resolve 21+.

Development

python src/server.py          # Compound server
python src/server.py --full   # Granular server
venv/bin/python tests/test_import.py
venv/bin/python scripts/audit_api_parity.py

Release and validation rules are in docs/process/release-process.md. AI agents working in this repository should start with AGENTS.md; Claude Code users can also read CLAUDE.md, which points to the same canonical instructions.

Author

Samuel Gursky (samgursky@gmail.com)

FAQ

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