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thenavidm

ScrapeCreators MCP Server

by thenavidm

Playlist

youtube_playlist

Retrieves all videos in a YouTube playlist by list ID, including playlist title, owner, count, and per-video details.

Instructions

Retrieves all videos in a YouTube playlist, including the playlist title, owner info, total video count, and each video's title, URL, thumbnail, duration, and channel. Accepts the playlist ID found in the 'list' URL parameter. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoNamed private ScrapeCreators account; selects credentials, not a remote account ID.
confirmNoMust be true for the specific approved credit-consuming research call.
playlist_idYesThe ID of the YouTube playlist. In the YouTube URL it will be the 'list' parameter.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With annotations present, the description adds meaningful context beyond them: credit consumption, the required confirm flag, and an explicit explanation that the read-like POST does not publish to social platforms (which reconciles the otherwise puzzling readOnlyHint=false). It still doesn't describe pagination behavior or result-size limits for large playlists.

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?

Return payload is front-loaded in the first sentence, with the parameter hint and the credit/confirm caveats following. Three sentences, each doing work, with only mild redundancy between the 'confirm=true' mention and the read-like POST clarification.

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?

There is no output schema, so listing the returned fields is genuinely necessary and it does so. With a 100% schema and annotations covering safety, the only remaining gap is pagination/volume behavior for large playlists.

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%, and the description largely restates the schema's own note that playlist_id is the YouTube URL 'list' parameter. The confirm requirement is surfaced, but no additional syntax or format detail is offered, so this sits at the baseline for a fully documented schema.

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 names a specific verb and resource ('Retrieves all videos in a YouTube playlist') and enumerates the returned fields, so the agent knows exactly what it gets back. It does not differentiate itself from the closest sibling, youtube_channel_playlists (which lists playlists rather than their contents), so an agent must infer the boundary.

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?

It states a hard invocation precondition ('requires confirm=true') and warns about paid credits, which is real usage guidance. However, it never says when to prefer this over youtube_channel_playlists or youtube_channel_videos, so alternative selection is left to inference.

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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