# davinci-resolve-mcp

> davinci-resolve-mcp — sandraschi-davinci-resolve-mcp. Use this tool when you need to automate DaVinci Resolve timeline and Fairlight tasks, solving inefficiencies in video editing workflows. It provides an interface for agent control, accepting inputs via FastMCP and outputting automated edits, ideal for streamlining post-production processes. Utilize it in contexts where repetitive tasks hinder productivity, such as large-scale video editing projects.

Canonical page: https://skillsregistry.net/skills/sandraschi-davinci-resolve-mcp  
JSON: https://api.skillsregistry.net/v1/skills/sandraschi-davinci-resolve-mcp

## Description

DaVinci Resolve timeline/Fairlight automation via FastMCP — agent control of the NLE. For Cursor / Claude Desktop. Webapp.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/sandraschi/davinci-resolve-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "sandraschi-davinci-resolve-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sandraschi-davinci-resolve-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sandraschi-davinci-resolve-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt