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llyfn

Spotify MCP Server

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Find tracks, albums, artists, playlists, shows, episodes, or audiobooks on Spotify. Apply filters by artist, album, track, year, genre, ISRC, or UPC.

Instructions

Search for tracks, albums, artists, playlists, shows, episodes, or audiobooks on Spotify.

    Args:
        query: Search query. Supports filters: artist:, album:, track:, year:, genre:,
            isrc: (track ISRC), upc: (album UPC). Use NOT/OR with quotes for refinement.
        types: Comma-separated types: track, album, artist, playlist, show, episode, audiobook.
        limit: Maximum results per type (1-50, default 10).
        offset: Index of first result to return (default 0).
        market: ISO 3166-1 alpha-2 country code to filter results.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
typesNotrack
limitNo
offsetNo
marketNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description should convey behavioral traits. It explains arguments but not pagination behavior (offset/limit imply pagination but no details), rate limits, or side effects. The output schema exists, reducing the need to describe returns, but more behavioral context would help.

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 a well-structured docstring with an 'Args' section. It is appropriately detailed but could be slightly more concise. Still, every sentence adds value.

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?

Given 5 parameters, required query, and an output schema, the description covers parameter semantics well. It does not discuss error handling or edge cases, but the output schema and parameter details provide sufficient context for an agent to invoke 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 description coverage is 0%, so the description must compensate. It does so thoroughly: explains query filters, types, limit, offset, and market. Each parameter's purpose and constraints are described, adding significant value 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?

The description clearly states the tool searches for various Spotify content types (tracks, albums, etc.), using specific verb 'Search for'. It distinguishes from sibling 'get_*' tools that retrieve specific items by ID.

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 description implies usage for finding content via queries but does not explicitly state when to use this tool versus alternatives like 'get_track' or 'get_album'. No when-not-to-use guidance is 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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