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jamiew

Spotify MCP Server

by jamiew

Top Artists and Tracks

get_top_items
Read-onlyIdempotent

Retrieve a user's top artists or tracks over a chosen time range. Use these results to profile musical taste and build recommendations.

Instructions

Get the user's top artists or tracks over a time range.

With /recommendations, audio-features and related-artists withdrawn from
third-party apps, this is the measured foundation for taste profiling and
building suggestions.

Args:
    item_type: 'tracks' or 'artists' (default 'tracks')
    time_range: 'short_term' (~4 weeks), 'medium_term' (~6 months) or 'long_term'
    limit: Max items to return (1-50, default 20)

Returns:
    TopItems with either 'tracks' or 'artists' populated

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
item_typeNotracks
time_rangeNomedium_term

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tracksNo
artistsNo
time_rangeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds useful behavioral detail beyond annotations: the valid time-range meanings, limit bounds, and that the return object will populate only one of 'tracks' or 'artists' based on item_type.

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?

The description is front-loaded with the core action and uses a compact Args/Returns structure. The context paragraph about withdrawn endpoints adds strategic value for selecting the tool, though it is not strictly required for invoking it. Overall, each section earns its place without padding.

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?

All three parameters are documented, the return shape is named, and annotations plus an output schema cover the remaining operational details. Minor gaps remain, such as not spelling out the time_range default in the description, but the schema fills that in. The tool can be called correctly from the description and existing structured data.

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 fully carries the parameter documentation. It explains every parameter in plain language: item_type values with default, time_range definitions with approximate durations, and limit range (1-50) with default. This goes well beyond the bare 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 states a specific verb and resource: 'Get the user's top artists or tracks over a time range.' It also clarifies the core toggle between item types. It does not explicitly differentiate itself from siblings such as get_recently_played or get_me, so it stops short of a 5.

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

Usage Guidelines4/5

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

The description gives clear context for when this tool matters: with recommendations, audio-features, and related-artists withdrawn, this is 'the measured foundation for taste profiling and building suggestions.' It does not list exclusions or alternative sibling tools, but the intended use case is clear.

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