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emit-ia

YouTube Transcript MCP Server

by emit-ia

youtube_batch_transcripts

Extract transcripts from multiple YouTube videos simultaneously to process content efficiently in bulk operations.

Instructions

Extract transcripts from multiple YouTube videos

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesArray of YouTube video URLs
languageNoLanguage code for transcriptsen
maxConcurrentNoMaximum number of concurrent requests
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('extract transcripts') but lacks critical details: it doesn't mention rate limits, error handling for invalid URLs, authentication requirements, output format, or whether the operation is read-only or has side effects. For a batch processing tool with no annotations, this is a significant gap in transparency.

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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action ('extract transcripts') and resource scope ('multiple YouTube videos'), making it easy to parse quickly. Every word earns its place, with no redundancy or fluff.

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

Completeness2/5

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

Given the tool's complexity (batch processing with concurrency control), lack of annotations, and no output schema, the description is incomplete. It doesn't address key aspects like what the output looks like (e.g., structured transcripts, error reports), performance implications of 'maxConcurrent,' or how it differs from other transcript tools. This leaves the agent under-informed for effective use.

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 input schema fully documents all three parameters (urls, language, maxConcurrent) with descriptions and defaults. The description adds no additional parameter semantics beyond implying batch processing via 'multiple YouTube videos,' which aligns with the 'urls' array parameter but doesn't provide extra context like URL format requirements or language code examples.

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 states the tool's purpose with a specific verb ('extract') and resource ('transcripts from multiple YouTube videos'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'youtube_get_transcript' (single video) or 'youtube_get_playlist_transcripts' (playlist-based), which handle similar transcript extraction but with different scopes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like batch processing multiple videos, compare it to single-video transcript tools, or specify prerequisites such as valid YouTube URLs. This leaves the agent without context for tool selection among the many sibling transcript-related tools.

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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