Skip to main content
Glama

youtube_search

Search public videos by keyword (~20 per page). Priced per page; defaults to 1 page.. Platform=youtube resource=search. Costs 1 credit(s). Requires Authorization: Bearer <api_key>. Credits unit: page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoPages to fetch. Defaults to 1.
keywordYesSearch text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose two meaningful traits: an auth requirement (Authorization: Bearer <api_key>) and a cost model (1 credit per page). It still omits rate limits, sorting/ordering behavior, and whether results are paginated beyond the stated depth, which keeps it short of a 5.

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

Conciseness3/5

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

The purpose and page size lead the sentence, which is good, but the tail is boilerplate redundancy: 'Priced per page' is restated by 'Costs 1 credit(s)' and 'Credits unit: page', and 'Platform=youtube resource=search' adds nothing for an agent. A stray double period also signals templated, unedited text.

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

Completeness3/5

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

For a two-parameter read tool with no output schema and no annotations, the description is adequate: auth, cost, and approximate result volume are present. It stops short of describing result fields, ordering, or how to disambiguate from the many sibling search/video tools, which is the main remaining gap.

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

Parameters3/5

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

Schema description coverage is 100%, so both parameters (keyword, depth) are already documented, and the description only restates the depth default and adds the ~20-per-page output estimate. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose4/5

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

States a specific verb+resource ('Search public videos by keyword') and adds scope via the ~20-per-page estimate, so an agent knows this is a keyword-driven public video search. It does not, however, distinguish itself from near siblings like youtube_videos, tiktok_search, or threads_search, leaving that routing to inference.

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

Usage Guidelines2/5

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

The only usage guidance is an implicit default page count; there is no statement of when to choose this over youtube_videos, youtube_channel, or other platform search tools, and no preconditions beyond the generic auth note.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources