Skip to main content
Glama
rubayatkhan

mcp-research-pipeline

by rubayatkhan

get_transcript

Retrieve a YouTube video's transcript by URL or ID for research and analysis. Supports language priority and optional HTML formatting for downstream processing.

Instructions

Fetch the transcript of a YouTube video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesYouTube URL or 11-character video ID.
languagesNoLanguage codes in priority order (default: ["en"]).
preserve_formattingNoKeep HTML formatting tags like <i> and <b>.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior, but it only says 'Fetch' and provides no detail about read-only behavior, transcript availability, language fallback, or error conditions. The agent is left to infer these traits.

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, front-loaded sentence with no filler. It is appropriately concise for a tool whose parameter and output schemas carry the detailed spec.

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 parameter schema and output schema cover the mechanical details, so the description does not need to restate them. However, with no annotations, the description omits behavioral context such as transcript availability and language handling, making this only minimally complete for an agent.

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 baseline is 3 even without parameter details in the description. The description itself adds no parameter-level meaning. The languages parameter's default is described as ["en"] while the schema default is null, but this inconsistency lives in the schema, not the description.

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 states a specific verb ('Fetch') and resource ('the transcript of a YouTube video'), making the tool's function immediately clear. It is easily distinguished from sibling tools like search_youtube, get_channel_videos, and get_playlist_videos.

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?

No guidance is given about when to use this tool over alternatives, nor any exclusions or prerequisites. The description only restates the operation without explaining scenarios like missing transcripts or how this relates to the other YouTube tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rubayatkhan/mcp-research-pipeline'

If you have feedback or need assistance with the MCP directory API, please join our Discord server