# DaVinci Resolve

> Use this tool when you need to automate video editing tasks or integrate natural language commands into your post-production workflow. DaVinci Resolve MCP Server enables AI assistants to interact with DaVinci Resolve, solving problems such as project management and timeline manipulation through its Python API. It accepts natural language inputs and outputs modified video editing projects, ideal for use cases where efficient and automated video editing is required.

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

## Description

DaVinci Resolve MCP Server enables AI assistants like Claude to directly interact with and control DaVinci Resolve through its Python API. Built by apvlv, the server provides tools for project management, timeline manipulation, media organization, and Fusion integration, allowing users to programmatically create, modify, and inspect video editing projects through natural language commands.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/davinci-resolve)
- **Repository:** <https://github.com/apvlv/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": "davinci-resolve"
    }
  }
}
```

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