Crawlora MCP

spotify_audiobook

Read-only

Fetch Spotify Web Player audiobook metadata by audiobook id or uri; Spotify exposes audiobook records through show URIs. Use spotify_audiobooks_search to find titles, spotify_audiobook_chapters for chapter lists, or spotify_chapter for one chapter.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "spotify_audiobook"
  }
}

Input Schema

Name	Required	Description
`id`	No	Spotify show ID, used when uri is omitted.
`uri`	No	Spotify audiobook/show URI or open.spotify.com/show/... URL.
`includeContentCapabilityTrait`	No	Include content capability trait fields when Spotify returns them.
`includeEpisodeContentRatingsV2`	No	Include episode content rating fields when Spotify returns them.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful behavioral context beyond the annotations: audiobook records are exposed through show URIs, which explains why the id parameter is a show ID. It does not mention auth needs or pagination, but an output schema exists.

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?

Two sentences, front-loaded with the core action and scoping detail, then the routing. Every clause earns its place and nothing is redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema handling return values and annotations covering the read-only, open-world profile, the description supplies the remaining essentials: what it returns, the id/uri duality, and how it relates to its three closest siblings. Nothing an agent needs to call it correctly is missing.

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 all four parameters are already documented, including the id-vs-uri relationship. The description only restates the id/uri choice without adding format or option semantics. Baseline 3 is appropriate when the schema carries the parameter burden.

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?

States a specific verb ('Fetch') plus resource ('Spotify Web Player audiobook metadata') and the two acceptable identifiers (id or uri). It explicitly distinguishes itself from sibling tools (search, chapters, chapter) so an agent can route correctly without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names three concrete alternatives and the condition that selects each: spotify_audiobooks_search to find titles, spotify_audiobook_chapters for chapter lists, spotify_chapter for a single chapter. This is explicit when-to-use-which routing with no inference required.

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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