YouTube MCP Server

get_playlist_items

Retrieve the videos contained in a YouTube playlist using its playlist ID, with options to set max results and page through additional items.

Instructions

Retrieve video items contained within a YouTube playlist.

Args: playlist_id: The ID of the playlist (e.g. 'PLrAXtmErZgOdP_8GzKt233nyGH51l50DH' or channel uploads ID). max_results: Number of items to retrieve (up to 50, default 20). page_token: Token for retrieving next page of results. raw: If True, returns unaltered raw YouTube Data API response.

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": {
      "playlist_id": "<playlist_id>"
    },
    "name": "get_playlist_items"
  }
}

Input Schema

Name	Required	Description	Default
`raw`	No
`page_token`	No
`max_results`	No
`playlist_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Sep 5, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses useful behavioral details: max_results caps at 50, page_token supports pagination, and raw returns the unaltered YouTube Data API response. It does not mention auth, rate limits, or side effects, but 'Retrieve' clearly signals a read-only operation.

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 compact and front-loaded with a one-sentence purpose, followed by a clean, scannable Args list. Every line contributes meaningful operational information with no filler.

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?

For a 4-parameter tool with an output schema, the description is largely complete: all parameters are documented, an example is given, and pagination plus raw-response behavior are covered. Minor gaps are lack of explicit sibling differentiation and absence of auth or rate-limit context, but those are not critical for this retrieval tool.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must explain all parameters and it does. It adds concrete meaning beyond the schema: playlist_id includes a real example and notes channel uploads IDs, max_results has an upper bound, page_token explains paging, and raw explains its effect on the response.

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 action and resource: 'Retrieve video items contained within a YouTube playlist.' This is specific and unambiguous, though it does not explicitly differentiate itself from sibling tools like design_binge_playlist or get_channel_rss_videos.

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 intended use is implied by the purpose statement and argument docs, but there is no explicit guidance about when to choose this tool over alternatives or any exclusions. An agent can infer usage from the name and description, but it is not directly stated.

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