# video2md

> video2md — metamol-video2md. Use this tool when you need to convert YouTube videos into Markdown documents for AI analysis, leveraging the Gemini API to extract insights from both audio and visuals. It solves the problem of making multimedia content accessible to AI models, enabling applications such as automated content analysis and summarization. Input a YouTube video, and output a Markdown document ready for AI processing and integration with git workflows.

Canonical page: https://skillsregistry.net/skills/metamol-video2md  
JSON: https://api.skillsregistry.net/v1/skills/metamol-video2md

## Description

Turn any YouTube video into an AI-readable Markdown document - audio and visuals - via the Gemini API

## Trust

- **Trust score (0–1):** 0.87
- **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/MetamoL/video2md)

## 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": "metamol-video2md"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/metamol-video2md` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/metamol-video2md/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