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Design, art and accessibility · MCP server

Davinci resolve MCP: MCP server, setup and security

Davinci resolve MCP is an open-source MCP server published on GitHub that lets an AI agent edit videos, grade colors, and manage media and DaVinci Resolve projects. Its repository has 3,735 stars and its last commit is from October 23, 2026 and it is licensed under MIT.

Actively maintainedTop 10% by stars

What Davinci resolve MCP does

According to its repository: “DaVinci Resolve integration for video editing, color grading, media management and project control.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Davinci resolve MCP is listed under Design, art and accessibility, a category of 95 servers in the directory, where it ranks #3 by stars.

Topics declared by the repository: blackmagic, blackmagic-design, blackmagicdesign, davinci-resolve, davinciresolve.

Installing and connecting Davinci resolve MCP

No package or remote server is declared in the official MCP registry: you install it from source, following the repository README.

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Python.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Davinci resolve MCP. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on March 18, 2025, the samuelgursky/davinci-resolve-mcp repository has 3,735 stars and 429 forks, with 3 open issues. It has more stars than 96% of the servers in the directory. It received changes this month.

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

Next AI Draw.ioNext AI Draw.io : 36.4K36.4KPascal 3D EditorPascal 3D Editor : 25.1K25.1KDavinci resolve MCPDavinci resolve MCP : 3.7K3.7KFigma MCP ServerFigma MCP Server : 2.1K2.1KMeiGen AI Design MCPMeiGen AI Design MCP : 1.8K1.8KTerraVisionTerraVision : 1.7K1.7KMeasureMeasure : 1.4K1.4KFigwrightFigwright : 1.2K1.2K
GitHub stars of the most followed servers in the category (log scale); Davinci resolve MCP in orange. Checked October 25, 2026.

Verdict

Davinci resolve MCP is one of the most solid servers in its category: followed, maintained and well framed.

Strengths

  • Active project: recent commit
  • Widely followed: 3.7K stars
  • Permissive licence (MIT)

Limitations

  • Install from source

Frequently asked questions

How do I install Davinci resolve MCP?

No package is declared in the MCP registry: clone the samuelgursky/davinci-resolve-mcp repository, follow its README, then declare the start command in your client's MCP configuration.

Is Davinci resolve MCP free?

The code is published under the MIT licence and can be used free of charge.

Is Davinci resolve MCP safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by samuelgursky on GitHub. Check who maintains it before giving it access.

What are the alternatives to Davinci resolve MCP?

In the same category: Pascal 3D Editor, Next AI Draw.io, Measure, and TerraVision.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score