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jkawamoto

YouTube Transcript MCP Server

by jkawamoto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_transcript

Retrieve a YouTube video's transcript by URL to enable text extraction and processing, with optional language selection and pagination for long transcripts.

Instructions

Retrieves the transcript of a YouTube video.

Input Schema

NameRequiredDescriptionDefault
urlYesThe URL of the YouTube video
langNoThe preferred language for the transcripten
next_cursorNoCursor to retrieve the next page of the transcript

Output Schema

NameRequiredDescriptionDefault
titleYesTitle of the video
transcriptYesTranscript of the video
next_cursorNoCursor to retrieve the next page of the transcript

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.8.3
    • changedInput schema / properties / next_cursor / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedOutput schema / properties / next_cursor / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observed

TDQS

C2.9/5.0
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 behavioral burden. It does not mention pagination behavior despite the next_cursor parameter, language fallback behavior, authentication requirements, rate limits, or error handling.

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

Conciseness4/5

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

The description is a single front-loaded sentence with no wasted words. It is efficient, though its terseness leaves important usage and behavioral context absent.

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 tool is simple and has a rich input schema plus an output schema, so the minimal description is partly sufficient. However, it omits sibling differentiation and behavioral details such as pagination, leaving clear gaps for an agent selecting among transcript-related tools.

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 already documents url, lang, and next_cursor. The description adds no parameter meaning beyond the schema, which matches the baseline of 3 when structured fields do 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?

The description states a specific verb and resource: retrieving a YouTube video transcript. It is clear what the tool does, but it does not distinguish itself from the sibling tool get_timed_transcript, which likely returns a timed variant.

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 gives no guidance on when to use this tool versus alternatives such as get_timed_transcript or get_available_languages. It only restates the action, leaving the agent to infer the selection context.

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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