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keenanbb

TIDAL MCP Server

by keenanbb

get_artist_radio

Generate a radio station of tracks similar to a specified artist's style using TIDAL's native recommendations. Input an artist ID to discover music that matches their sound.

Instructions

Get tracks similar to an artist's style (artist radio).

This returns TIDAL's native recommendations based on the specified artist, useful for discovering music in a similar style.

Args: artist_id: ID of the seed artist limit: Maximum tracks to return (default: 20, max: 100)

Returns: List of similar tracks with seed artist info

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
artist_idYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of tracks returned
statusYesOperation status (success/error)
tracksYesList of recommended tracks
seed_idYesID of the seed track or artist
seed_nameYesName of the seed track or artist
seed_typeYesType of seed (track/artist)

Implementation Reference

  • The core implementation of the get_artist_radio tool. Decorated with @mcp.tool() for automatic MCP registration. Handles authentication, fetches artist via tidalapi, retrieves radio tracks, maps to Track models, and returns structured RadioTracks response.
    @mcp.tool()
    async def get_artist_radio(artist_id: str, limit: int = 20) -> RadioTracks:
        """
        Get tracks similar to an artist's style (artist radio).
    
        This returns TIDAL's native recommendations based on the specified artist,
        useful for discovering music in a similar style.
    
        Args:
            artist_id: ID of the seed artist
            limit: Maximum tracks to return (default: 20, max: 100)
    
        Returns:
            List of similar tracks with seed artist info
        """
        if not await ensure_authenticated():
            raise ToolError("Not authenticated. Please run the 'login' tool first.")
    
        try:
            limit = min(max(1, limit), 100)
    
            # Get the seed artist first
            artist = await anyio.to_thread.run_sync(session.artist, artist_id)
            if not artist:
                raise ToolError(f"Artist with ID '{artist_id}' not found")
    
            # Get radio tracks
            radio_tracks = await anyio.to_thread.run_sync(
                lambda: artist.get_radio(limit=limit)
            )
    
            tracks = []
            for t in radio_tracks:
                tracks.append(
                    Track(
                        id=str(t.id),
                        title=t.name,
                        artist=t.artist.name if t.artist else "Unknown Artist",
                        album=t.album.name if t.album else "Unknown Album",
                        duration_seconds=t.duration,
                        url=f"https://tidal.com/browse/track/{t.id}",
                    )
                )
    
            return RadioTracks(
                status="success",
                seed_id=artist_id,
                seed_type="artist",
                seed_name=artist.name,
                count=len(tracks),
                tracks=tracks,
            )
        except ToolError:
            raise
        except Exception as e:
            raise ToolError(f"Failed to get artist radio: {str(e)}")
  • Pydantic BaseModel defining the output schema for the get_artist_radio tool (shared with get_track_radio). Specifies structure including seed info and list of Track objects.
    class RadioTracks(BaseModel):
        """Radio/recommendation tracks based on a seed track or artist."""
    
        status: str = Field(description="Operation status (success/error)")
        seed_id: str = Field(description="ID of the seed track or artist")
        seed_type: str = Field(description="Type of seed (track/artist)")
        seed_name: str = Field(description="Name of the seed track or artist")
        count: int = Field(description="Number of tracks returned")
        tracks: List[Track] = Field(description="List of recommended tracks")
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that this returns 'TIDAL's native recommendations' and mentions default/max values for the limit parameter, which adds useful behavioral context. However, it doesn't cover important aspects like rate limits, authentication requirements, or pagination behavior.

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 perfectly structured and concise. It starts with the core purpose, adds context about TIDAL's native recommendations, then provides clear parameter documentation. Every sentence earns its place with no wasted words.

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 the tool's moderate complexity, no annotations, and the presence of an output schema, the description is reasonably complete. It explains what the tool does, provides parameter semantics, and mentions the return format. However, for a tool with no annotations, it could benefit from more behavioral context about authentication or rate limits.

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

Parameters4/5

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

With 0% schema description coverage, the description must compensate. It provides meaningful semantics for both parameters: 'artist_id: ID of the seed artist' and 'limit: Maximum tracks to return (default: 20, max: 100)'. This adds significant value beyond the bare schema, though it doesn't explain the format of artist_id values.

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's purpose with specific verbs ('Get tracks similar to an artist's style') and identifies the resource ('artist radio'). It distinguishes from siblings like 'get_track_radio' by specifying artist-based recommendations rather than track-based ones.

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 provides clear context about when to use this tool ('useful for discovering music in a similar style'), but doesn't explicitly mention when not to use it or name specific alternatives among the sibling tools. It implies usage for artist-based recommendations without explicit exclusions.

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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