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alex2zimmermann-ux

YouTube Transcript MCP Server

search_transcript

Read-only

Find specific keywords or phrases within YouTube video transcripts and retrieve matching segments with timestamps for targeted content review.

Instructions

Search for keywords or phrases in a YouTube video transcript and return matching segments with timestamps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL or video ID to search in
queryYesSearch query string (case-insensitive keyword or phrase to find in the transcript)
languageNoISO 639-1 language code for the transcript (e.g. en, de, es, fr)en
context_segmentsNoNumber of surrounding transcript segments to include as context around each match

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering safety and scope. The description adds valuable context about case-insensitive search and timestamp returns, which aren't covered by annotations. However, it doesn't mention potential limitations like transcript availability or search performance.

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 a single, well-structured sentence that efficiently communicates the tool's core functionality without any wasted words. It's front-loaded with the main purpose and includes essential details about the output format.

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?

Given the presence of annotations covering safety/scope, 100% schema coverage, and an output schema (which handles return values), the description provides adequate context. It could be slightly more complete by mentioning transcript availability constraints or search result formatting, but covers the essential purpose well.

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 fully documents all parameters. The description mentions 'keywords or phrases' which aligns with the 'query' parameter but doesn't add meaningful semantics beyond what's already in the schema descriptions. Baseline 3 is appropriate when schema does the heavy lifting.

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 clearly states the specific action ('Search for keywords or phrases'), the resource ('in a YouTube video transcript'), and the output ('return matching segments with timestamps'). It distinguishes from sibling tools like 'get_transcript' (which retrieves full transcripts) and 'get_transcript_summary' (which provides summaries) by focusing on targeted search functionality.

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?

The description implies usage for keyword/phrase searches in transcripts, but doesn't explicitly state when to use this tool versus alternatives like 'get_transcript' for full transcripts or 'batch_transcripts' for multiple videos. It provides basic context but lacks explicit guidance on tool selection or exclusions.

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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