YouTube Research
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.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- social-media
- Source
- PulseMCP
- Repository
- github.com/danhilse/youtube_research_mcp
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve YouTube Research from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.