Skip to main content
Glama
mohamdben-yahia

YouTube MCP Server

find_content_gaps

Discover content gaps by analyzing top search results for outdated videos. Uncover low-competition keywords that new channels can target with fresh updates.

Instructions

Identify high-demand content gaps and low-competition keyword opportunities.

Finds topics where top search results are outdated (2+ years old), signaling easy ranking opportunities for a new channel to displace them with a fresh 2026 update.

Args: niche_or_topic: Topic, query, or question to analyze (e.g. 'how to learn sql for data analysis'). max_results: Number of search results to inspect (default 15). region_code: ISO country code (default 'US').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNo
region_codeNoUS
niche_or_topicYes

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

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the key heuristic (2+ year old top results, fresh 2026 relevance), which is useful behavioral context. However, it does not clarify whether this performs a live search, how results are scored, or any rate or data-source limitations. For a read-only research tool this is adequate but not rich.

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 description is compact, well-organized, and front-loaded with the core purpose. The method explanation and Args block each add distinct value with no filler or redundancy.

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?

With an output schema present, return values do not need explanation. Parameters are well covered, and the tool's purpose and heuristic are clear. The only minor gap is the absence of explicit guidance on when to choose this tool over sibling research tools, but the strong purpose statement largely compensates for that.

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?

Despite schema_description_coverage being 0%, the description documents all three parameters clearly: niche_or_topic with an example, max_results with a default, and region_code with default and format. This fully compensates for the missing schema descriptions.

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 description states a specific verb ('Identify') and a well-defined resource ('content gaps' / 'low-competition keyword opportunities'), then adds a concrete criterion: top search results are outdated (2+ years old). This distinguishes it from sibling tools like get_trending_niches or scout_niche_channels, which focus on different aspects of niche research.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool: when the goal is finding high-demand content gaps and easy ranking opportunities for a new channel. It does not explicitly name alternatives or state when not to use it, but the use case is specific and well implied.

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