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Glama

YouTube Transcript & Search MCP Server

Search YouTube

search_youtube
Read-only

Search YouTube for videos or channels. Paginate by passing next_page_token from the previous result. has_more tells you whether another page exists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSearch query (required unless paginating)
typeNoDefault 'video'
limitNoResults per page, 1-50 (default 20)
next_page_tokenNoToken from a previous result

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
has_moreNo
next_page_tokenNo

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already indicate readOnly and open-world behavior, so the safety profile is covered. The description adds meaningful behavioral detail about pagination, telling the agent to pass next_page_token and to use has_more to detect another page. This goes beyond the annotations without contradicting them.

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 two concise sentences. The first states the core action, and the second delivers essential pagination behavior with zero filler or repetitive phrasing.

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?

The description is adequate for a read-only, paginated search tool with a full output schema. The main gap is that it does not contextualize the tool relative to sibling search tools, which creates ambiguity for an agent choosing among search_youtube, search_channel_videos, and search_playlist_videos.

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 the schema alone already explains q, type, limit, and next_page_token. The description adds some context on how next_page_token and has_more work together for pagination, but it does not add significant meaning beyond what the schema describes.

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?

The description clearly identifies the action ('Search YouTube') and resource scope ('videos or channels'). However, it does not explicitly differentiate itself from sibling tools that also have 'search' in their names, such as search_channel_videos or search_playlist_videos, so it stops short of perfect clarity.

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 description explains how pagination works but gives no guidance on when to use this general YouTube search versus the more specific sibling search tools. It never mentions alternatives, exclusions, or the nuance that q may be required unless paginating.

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

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TDQS

A4.1/5.0
Disambiguation4/5

Most tools target a distinct resource and action: search, list, metadata, transcript, job lifecycle, and credits. The get_transcripts_job / get_transcripts_result / get_transcripts_results trio is easy to blur at first glance, but the descriptions clearly differentiate job status, one result, and paged results.

Naming Consistency4/5

The set mostly follows a predictable verb_noun pattern: get_, list_, search_, submit_, cancel_. The main deviation is latest_channel_videos, which uses an adjective instead of a verb, and the result/results pair is mildly confusing, but overall naming is coherent and easy to navigate.

Tool Count5/5

14 tools is well within the sweet spot for a server with this scope. Each tool serves a clear niche: video lookup, metadata, single transcripts, batch jobs, and search are all represented without unnecessary or redundant tools.

Completeness5/5

The server provides full coverage of the transcript and search workflow: search YouTube, list channel/playlist videos, fetch or batch-fetch transcripts, check job progress/credits, and read results. There are no obvious missing operations that would force an agent into a dead end.