Outliers first
Start with what already beat the baseline.
Claude Code
Give Claude Code real YouTube research before it writes.
Let Claude Code call Autonolab tools while it builds briefs, research docs, scripts, dashboards, and creator automations.
Agent prompt
Use Autonolab MCP to research a niche, then create a markdown content strategy for the repo.
Launch limits
Free: 20/day and 5/min. Hobby: 100/day. Pro: 200/day.
Creator strategy data
Niche Finder, Niche Explorer, Channel Audit, channels, and videos in one layer.
Agent-ready
Use REST endpoints or the remote MCP server.
MCP tool calls
The same tools are available through API calls and MCP tool calls, so you can use the interface that fits your agent stack.
MCP
POST /mcp
Tools for outliers, channels, audits, videos, and niche finding.
REST
POST /api/v1/youtube/outliers
Grouped outlier videos by keyword.
REST
POST /api/v1/youtube/niche-explorer/channels
Niche Explorer enriched channel opportunities.
REST
POST /api/v1/youtube/channel-audit
Channel Audit deep research AI agent output.
REST
POST /api/v1/youtube/niche-finder
Niche Finder deep research AI agent output.
Built for creator questions, not raw video lists.
Raw YouTube data is only the first layer. Autonolab is organized around the questions creators and agents actually ask: what worked, why it worked, where the opportunity is, what Niche Explorer channels prove, what Niche Finder recommends, and what the Channel Audit deep research AI agent says to create next.
MCP tools included
- find_youtube_outliers
- search_niche_channels
- get_channel_videos
- audit_youtube_channel
- find_youtube_niche