MCP YouTube Intelligence

get_transcript

Extract transcripts from YouTube videos with options for concise summaries, full text, or segmented chunks to analyze video content efficiently.

Instructions

Get video transcript. mode: 'summary' (default, ~300 tokens), 'full' (saves to file, returns path), 'chunks' (split into segments).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "video_id": "<video_id>"
    },
    "name": "get_transcript"
  }
}

Input Schema

Name	Required	Description	Default
`video_id`	Yes	YouTube video ID
`mode`	No		summary
`llm_provider`	No	LLM provider for summary (default: auto)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.3Feb 18, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: default mode, token length for summary (~300), file-saving behavior for 'full' mode, and segmentation for 'chunks'. However, it doesn't mention rate limits, authentication needs, error conditions, or what happens with invalid video IDs.

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?

Extremely concise and front-loaded: the first three words state the core purpose, followed by efficient mode explanations. Every sentence earns its place by providing essential operational details without redundancy.

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 3-parameter tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers mode behaviors well but lacks information about return values (beyond 'returns path' for full mode), error handling, or performance characteristics that would help an agent use it correctly.

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

Parameters4/5

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

Schema description coverage is 67% (2 of 3 parameters have descriptions). The description adds significant value beyond the schema: it explains what each 'mode' does (summary length, file saving for full, segmentation for chunks) and clarifies the default behavior. This compensates well for the schema's partial coverage.

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: 'Get video transcript' with specific modes. It distinguishes from siblings like 'get_video' (metadata) and 'search_transcripts' (searching). However, it doesn't explicitly contrast with 'segment_topics' which might overlap with 'chunks' mode.

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 when to use different modes ('summary' for brief, 'full' for complete, 'chunks' for segmented), but doesn't provide explicit guidance on when to choose this tool over alternatives like 'search_transcripts' or 'get_video'. No exclusions or prerequisites are mentioned.

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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