Skip to main content
Glama
mohamdben-yahia

YouTube MCP Server

find_breakout_growth_channels

Identify recently created YouTube channels with rapid subscriber growth in a chosen niche, enabling early detection of breakout creators and emerging trends.

Instructions

Find modern breakout channels created recently that grew rapidly from scratch.

Discovers new channels that recently solved the YouTube algorithm rather than legacy giants.

Args: niche: Topic or niche keyword (e.g. 'ai automation', 'finance beginners'). max_channel_age_months: Maximum channel age in months (default 24). min_subscribers: Minimum subscribers (default 1000). max_subscribers: Maximum subscribers (default 300000). region_code: ISO country code (default 'US'). max_results: Max results to return (default 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nicheYes
max_resultsNo
region_codeNoUS
max_subscribersNo
min_subscribersNo
max_channel_age_monthsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It adds useful behavior context such as recency and growth-from-scratch, but doesn't specify result ordering, the precise growth threshold, or edge-case behavior. The read-only nature is implied by 'Find' and there is no contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The tool is described in two purposeful sentences followed by a scannable Args list; there is no fluff or repetition. Front-loading the core action makes it easy for an agent to match intent quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

All input parameters are covered and an output schema exists, so missing return-value documentation is not a concern. The only notable gap is that 'grew rapidly' is not formally defined beyond the age/subscriber filters, and no alternative tool routing is given.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the Args block is essential and it delivers: every one of the six parameters is explained, including niche example, age bound, subscriber range, ISO country code, and max results. This goes well beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence names a clear action and object: find modern breakout channels created recently and grown rapidly from scratch. The second sentence strengthens differentiation by explicitly excluding legacy giants and framing the tool around channels that recently solved the YouTube algorithm.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It conveys the main use case (young, fast-growing channels) and mentions what it is not (legacy giants), but it never names sibling alternatives or says when to prefer this over scout_niche_channels or general search tools. The agent must infer routing from context rather than explicit guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mohamdben-yahia/youtube-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server