Spotify & TMDB Web MCP Server

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create_actor_playlist

Creates a Spotify playlist from an actor's filmography by finding movie soundtrack songs and adding matching tracks automatically.

Instructions

End-to-End Pipeline: Discover an actor's filmography via TMDB/DDG, locate songs on Spotify, create a new playlist, and add all tracks.

Args: actor_name: Name of the actor (e.g., 'Cillian Murphy', 'Shah Rukh Khan', 'Keanu Reeves') playlist_name: Optional custom name for the playlist max_movies: Number of movies to pull songs from (default: 10) max_songs_per_movie: Number of songs to add per movie (default: 3) specific_movies: Optional comma-separated list of specific movies to use (e.g. 'Inception, Dunkirk, Oppenheimer') sort_by: Filmography sort order ('popularity' or 'release_date', default: 'popularity') public: Whether the created playlist is public (default: True)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "actor_name": "<actor_name>"
    },
    "name": "create_actor_playlist"
  }
}

Input Schema

Name	Required	Default
`public`	No
`sort_by`	No	popularity
`actor_name`	Yes
`max_movies`	No
`playlist_name`	No
`specific_movies`	No
`max_songs_per_movie`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 6, 2026

TDQS

A4.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false, and destructiveHint=false, so the safety profile is partly covered. The description adds real value by naming the three external services (TMDB, DDG, Spotify) and the ordered pipeline stages, but it says nothing about Spotify auth/write scope, rate limits, or what happens on partial failure mid-pipeline (e.g., playlist created but some tracks missing).

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?

Front-loaded with the pipeline summary, then a clean arg list. Some entries merely restate schema titles and defaults, but the added examples and enum values justify the space, so there is little true waste.

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?

For a 7-parameter multi-service pipeline with an output schema, the definition covers the flow and every argument adequately. Remaining gaps are behavioral rather than structural: no guidance on failures, deduplication, or naming collisions, which matter given the non-idempotent, side-effecting nature of the call.

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 carries the full burden and does it: all seven parameters are documented with meaning, defaults, and concrete examples ('Cillian Murphy', 'Inception, Dunkirk, Oppenheimer'). Notably it supplies the allowed values for sort_by ('popularity' or 'release_date'), which the schema itself leaves as an unconstrained string.

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 first sentence names a specific verb chain and resource: discover an actor's filmography via TMDB/DDG, locate songs on Spotify, create a playlist, add tracks. It is immediately distinguishable from granular siblings like create_playlist, search_actor_movies, and add_tracks_to_playlist because it is explicitly framed as the composed end-to-end pipeline.

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 phrase 'End-to-End Pipeline' tells the agent this tool covers the whole flow, implying it should be preferred over chaining the single-step siblings. However, it never says so explicitly, nor does it state when to avoid it (e.g., when a playlist already exists or when the user only wants discovery or only wants tracks added).

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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