# YouTube Data API

> Use this tool when you need to access and analyze YouTube data efficiently, solving problems such as video search, channel statistics, and content trend analysis. It provides token-optimized responses and MongoDB caching, accepting inputs like search queries and channel IDs, and outputting structured data on video performance, engagement ratios, and trending content. Ideal for content creators, marketers, and researchers seeking to discover emerging channels and topics without navigating the complexities of the YouTube API.

Canonical page: https://skillsregistry.net/skills/kirbah-youtube  
JSON: https://api.skillsregistry.net/v1/skills/kirbah-youtube

## Description

YouTube MCP server by Kiryl Bahdanau that provides AI assistants with efficient access to YouTube data through the YouTube Data API v3, featuring token-optimized responses and MongoDB caching for performance. Built with TypeScript and the Model Context Protocol SDK, it offers tools for video search, channel statistics, trending content analysis, transcript extraction with key segment filtering, and an advanced niche analysis system that identifies emerging channels with consistent high-performance content. The implementation includes API quota tracking, engagement ratio calculations, and a sophisticated multi-phase analysis pipeline for discovering promising YouTube channels within specific topics and timeframes. Designed for content creators, marketers, and researchers who need structured YouTube data analysis without manually navigating the complexities of the YouTube API.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kirbah-youtube)
- **Repository:** <https://github.com/kirbah/mcp-youtube>

## 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": "kirbah-youtube"
    }
  }
}
```

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