YouTube Knowledge
Transforms YouTube into a queryable knowledge source through five specialized tools for video search, detailed content analysis, trending discovery, channel research, and AI-powered content insights. Built with intelligent quota management and multi-tier caching (Redis/memory) to optimize YouTube Data API usage, the implementation includes transcript extraction via web scraping, comment sentiment analysis, and optional LLM integration with OpenAI/Anthropic for advanced features like learning path generation, knowledge graph creation, and content simplification. Features automatic quota optimization, fallback mechanisms for API limits, and comprehensive analytics tracking, making it valuable for content creators researching competitors and trends, educators building learning curricula from video content, and researchers analyzing YouTube discourse patterns and audience engagement metrics.
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 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/efikuta/youtube-knowledge-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve YouTube Knowledge 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.