yt-outlier-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| YOUTUBE_API_KEY | Yes | YouTube Data API v3 key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| find_outliersA | Search YouTube for a topic phrase and return videos on small channels that hugely outperform the channel's subscriber base and its own recent uploads — evidence the FORMAT drove the views (replicable by a new channel), not an existing audience. Defaults encode the Icon Method criteria: ≥100K views, channel ≤100K subs, ≥5:1 views:subs, uploaded within the last year. Costs ~110-130 YouTube API quota units per call (free daily quota: 10,000). |
| get_video_structureA | Fetch what makes an outlier video's format copyable: duration, chapters (parsed from the description), tags, and the transcript. Icon Method verification step: extract the structure, don't guess it. Costs 1 YouTube API quota unit (transcript is fetched outside the API at zero quota and may be unavailable for some videos). |
| get_comment_signalA | Fetch a video's top comments (relevance-ordered) plus simple demand metrics: how many ask questions and how many use demand phrasing ('please make...', 'part 2', 'how do you...'). Icon Method verification step: comments prove the topic has unmet demand, not just views. Costs 1 YouTube API quota unit. |
| search_niche_sweepA | Run the outlier search once per niche by substituting each niche into a phrase template (e.g. "beginner mistakes {niche}" across ['sourdough', 'bonsai', 'leathercraft']) and rank the hits across all niches. Answers: which hobby cluster has a replicable breakout format right now? EXPENSIVE: each niche costs a full search (~110-130 quota units), so an 8-niche sweep uses ~10% of the 10,000-unit daily free quota. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct step in the outlier analysis workflow: finding outliers, analyzing comments, extracting video structure, and running batch niche searches. No two tools overlap in purpose.
All tool names follow a consistent verb_noun pattern in snake_case (find_outliers, get_comment_signal, get_video_structure, search_niche_sweep), making them predictable.
With 4 tools, the set is slightly lean but appropriate for a specialized YouTube outlier analysis server. Each tool addresses a core function without unnecessary redundancy.
The tools cover the main outlier identification and validation pipeline: search, comment analysis, and structure extraction. Missing channel-level details or result persistence are minor gaps given the focused scope.