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nlevy

Spotify MCP Server

by nlevy

get_user_top_artists

Retrieve your top artists on Spotify by time range (last 4 weeks, 6 months, or years). Optionally set limit and offset to control results. Returns artist name, popularity, followers, genres, and more.

Instructions

Get user's top artists from Spotify

Arguments: time_range (str, optional): Time period for top artists (default: "medium_term") - "short_term": Last 4 weeks - "medium_term": Last 6 months
- "long_term": Several years limit (int, optional): Maximum number of artists to return (default: 20, max: 50) offset (int, optional): Index of the first artist to return (default: 0)

Returns: Dict[str, Any]: - success (bool): Whether the operation was successful - artists (List[Dict]): List of artist objects containing: - id (str): Spotify artist ID - name (str): Artist name - popularity (int): Artist popularity score (0-100) - followers (int): Number of followers - genres (List[str]): List of genres - spotify_url (str): Spotify profile URL - images (List[Dict]): Artist images with url, height, width - time_range (str): Time range used for the query - total_artists (int): Number of artists returned - message (str): Success message - error (str, optional): Error message if failed

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
time_rangeNomedium_term
limitNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses return format and parameter effects but does not mention authentication requirements or that it uses the current user's listening history. This is a significant gap for a user-specific endpoint.

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?

Description is well-structured with clear sections for arguments and returns. Information is front-loaded and concise, with no extraneous content.

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?

The description covers all three optional parameters and details the return structure comprehensively. Given the low complexity and presence of an output schema, this description is fully adequate for using the tool correctly.

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 coverage is 0%, but description comprehensively explains all three parameters: time_range with its three enum-like values, limit with default and max, offset with default. This adds necessary meaning beyond the schema.

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?

Description clearly states 'Get user's top artists from Spotify' with specific verb and resource. It is easily distinguished from sibling tools like get_user_top_tracks and search_artists.

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?

Description explains what the tool does but does not provide explicit guidance on when to use it vs alternatives. It relies on the context of sibling tool names, but no direct comparison or when-not-to-use instructions are given.

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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