LibreAI / Vidéo / davinci-resolve-mcp
// video · samuelgursky/davinci-resolve-mcp

davinci-resolve-mcp

davinci-resolve-mcp est un projet de vidéo open source, créé par samuelgursky (samuelgursky/davinci-resolve-mcp sur GitHub). Il compte 3 410 étoiles sur GitHub et 397 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.

An MCP server that lets AI agents drive DaVinci Resolve Studio — editing, grading and more.

★ 3,4 k étoiles⑂ 397 forksMITmis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
3 410
Forks
397
Licence
MIT
Dernière mise à jour sur GitHub
8 octobre 2026
Catégorie
Vidéo
Type de fiche
Guide d'installation complet
// fonctionnement

Comment ça marche

  1. Clarify your goal

    Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.

  2. Get the project

    Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.

  3. Install and configure

    Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.

  4. Run your first task

    Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.

// fonctionnalités

Pourquoi on l'adore

Broad Resolve control

Drive projects, timelines, edits and colour work in DaVinci Resolve through MCP tools.

Free-edition bridge

An in-app bridge script (Workspace > Scripts > resolve_bridge) works where the external scripting API is unavailable.

Local control panel

A local control panel UI for inspecting and controlling the server.

Verified-trap guard

Guardrails that catch destructive or wrong-target operations before they run.

Execution traces

Agent execution traces explain each editing decision for review.

Source media safety

A documented security posture and source-media safety rules for professional footage.

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// lancez-le

Lancez-le vous-même

  1. Clone the repository

    Get the source so you can inspect, configure and run it locally.

    git clone https://github.com/samuelgursky/davinci-resolve-mcp.git
    cd davinci-resolve-mcp
  2. Quick setup with npx

    Run the setup command, which installs and configures the server.

    npx davinci-resolve-mcp setup
  3. Or install from source

    Clone, run the installer, install the Resolve bridge, then restart Resolve and open a project.

    git clone https://github.com/samuelgursky/davinci-resolve-mcp.git
    cd davinci-resolve-mcp
    python install.py
    python scripts/install_resolve_bridge.py
// cas d'usage

Ce que vous pouvez créer

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// faq

Questions fréquentes

Who maintains davinci-resolve-mcp?

It is maintained by samuelgursky on GitHub (samuelgursky/davinci-resolve-mcp), where the source, issues and releases live.

Is it free to use?

Yes — it is free and open source under the MIT licence, which permits use, modification and redistribution, including commercially, with attribution.

Does it need a paid API key?

The MCP server is free; you need DaVinci Resolve installed (the bridge targets the free edition, Studio unlocks the full scripting API) and your MCP client's own model access.

How does it compare to manual editing only, or generic desktop automation?

Compared with manual editing only, or generic desktop automation, davinci-resolve-mcp's distinguishing focus is: an MCP server that lets AI agents drive DaVinci Resolve Studio — editing, grading and more. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.

How do I get started?

Clone https://github.com/samuelgursky/davinci-resolve-mcp (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.

// continuez l'exploration

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