# YouTube Research

> Use this tool when you need to efficiently gather video content on specified topics or perform trend analysis, as it integrates with the YouTube API to perform aggregated video searches and compiles results with metadata. It solves problems related to content curation, research, and analysis by abstracting YouTube search complexities. The tool takes user topics as input and outputs compiled video results with metadata, making it ideal for use cases such as creating themed playlists or gathering educational resources.

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

## Description

This YouTube research MCP server, developed by an unnamed author, integrates with the YouTube API to perform aggregated video searches. Built with TypeScript and leveraging the Model Context Protocol SDK, it uses sampling to generate search queries from user topics, fetches both short and long videos, and compiles results with metadata. The server implements sequential thinking, logging each step as separate 'thoughts' for operational visibility. By abstracting YouTube search complexities, it enables AI assistants to efficiently gather video content on specified topics. This implementation is particularly useful for content curation, trend analysis, and research tasks, facilitating use cases such as creating themed playlists, analyzing video popularity across topics, or gathering educational resources.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** social-media
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/danhilse-youtube-research)
- **Repository:** <https://github.com/danhilse/youtube_research_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": "danhilse-youtube-research"
    }
  }
}
```

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