Spotify MCP Server
Seamlessly connect FlowHunt AI workflows to Spotify for advanced music playback, search, playlist, and queue management with the Spotify MCP Server.

What does “Spotify” MCP Server do?
The Spotify MCP (Model Context Protocol) Server is a tool designed to connect AI assistants, such as LLMs, with Spotify’s extensive API. By acting as an intermediary, it allows AI-powered workflows to control Spotify playback, search for tracks, albums, artists, or playlists, retrieve detailed information, and manage user playlists and queues. This capability enables developers and AI users to seamlessly integrate music data and playback control into their applications, automating music management, curation, and exploration tasks. It enhances development workflows by providing standardized access to Spotify’s features, making it easier to build intelligent agents that interact dynamically with music content.
List of Prompts
No prompt templates are mentioned in the repository.
List of Resources
No explicit MCP resources are documented in the repository.
List of Tools
- Start Playback: Initiates playback of a track or playlist on the connected Spotify account.
- Pause Playback: Pauses the current playback session.
- Skip Playback: Skips to the next track in the playback queue.
- Search: Allows searching for tracks, albums, artists, or playlists.
- Get Info: Retrieves information about a specific track, album, artist, or playlist.
- Manage Queue: Adds tracks to the Spotify playback queue.
- Manage Playlists: Enables creation and updating of user playlists.
Use Cases of this MCP Server
- Music Playback Control: Automate and control playback directly through AI, such as playing or pausing music, skipping tracks, or managing the queue, greatly benefiting hands-free or workflow-driven environments.
- Music Discovery and Search: Allow AI agents to search the Spotify catalog for songs, albums, artists, or playlists, enabling recommendation engines or music exploration features within apps.
- Playlist Management: Enable intelligent agents to create, update, and curate playlists for users, supporting personalized recommendations and routine playlist updates.
- Music Information Retrieval: Fetch detailed metadata about tracks, albums, artists, or playlists, which can be used for music analysis, reporting, or context-aware recommendations.
- Queue Management: AI can dynamically manage and update the playback queue, adding or removing tracks in response to user preferences or contextual cues.
How to set it up
Windsurf
No Windsurf-specific setup instructions are provided.
Claude
- Prerequisite: Obtain Spotify API credentials (Client ID, Client Secret, Redirect URI) from Spotify Developer Dashboard.
- Clone the Repository:
git clone https://github.com/varunneal/spotify-mcp.git
- Edit Configuration File: Open the Claude Desktop config file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:
%APPDATA%/Claude/claude_desktop_config.json
- macOS:
- Add the MCP Server: Insert the following JSON snippet in the
mcpServers
section:"spotify": { "command": "uv", "args": [ "--directory", "/path/to/spotify_mcp", "run", "spotify-mcp" ], "env": { "SPOTIFY_CLIENT_ID": "YOUR_CLIENT_ID", "SPOTIFY_CLIENT_SECRET": "YOUR_CLIENT_SECRET", "SPOTIFY_REDIRECT_URI": "http://127.0.0.1:8080/callback" } }
- Save and Restart: Save the file and restart Claude Desktop.
- Verify: Confirm that the Spotify MCP server is available in the Claude interface.
Cursor
No Cursor-specific setup instructions are provided.
Cline
No Cline-specific setup instructions are provided.
Securing API Keys
API credentials are stored via environment variables in the configuration JSON:
"env": {
"SPOTIFY_CLIENT_ID": "YOUR_CLIENT_ID",
"SPOTIFY_CLIENT_SECRET": "YOUR_CLIENT_SECRET",
"SPOTIFY_REDIRECT_URI": "http://127.0.0.1:8080/callback"
}
How to use this MCP inside flows
Using MCP in FlowHunt
To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:
{
"spotify": {
"transport": "streamable_http",
"url": "https://yourmcpserver.example/pathtothemcp/url"
}
}
Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “spotify” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.
Overview
Section | Availability | Details/Notes |
---|---|---|
Overview | ✅ | |
List of Prompts | ⛔ | No prompt templates found |
List of Resources | ⛔ | No explicit resources found |
List of Tools | ✅ | Inferred from README feature list |
Securing API Keys | ✅ | Via env in JSON configuration |
Sampling Support (less important in evaluation) | ⛔ | Not mentioned |
Our opinion
The Spotify MCP server offers practical music integration capabilities, with clear setup for Claude and comprehensive tool support for playback and search. However, the absence of prompt templates, explicit resources, and roots/sampling support lowers its extensibility for advanced MCP users.
MCP Score
Has a LICENSE | ✅ (MIT) |
---|---|
Has at least one tool | ✅ |
Number of Forks | 69 |
Number of Stars | 358 |
Frequently asked questions
- What does the Spotify MCP Server do?
It enables FlowHunt AI agents and workflows to connect with Spotify’s API for playback control, searching music, managing playlists and the queue, and accessing metadata—automating music-related tasks programmatically.
- What tools are available via the Spotify MCP Server?
Available tools include Start Playback, Pause Playback, Skip Playback, Search (tracks, albums, artists, playlists), Get Info, Manage Queue, and Manage Playlists.
- How do I secure my Spotify API credentials?
Store your Spotify API credentials as environment variables in the MCP server configuration JSON under the 'env' field. Never commit sensitive credentials to source control.
- Can FlowHunt use the Spotify MCP Server for playlist management?
Yes, FlowHunt can use the MCP Server to create, update, and curate Spotify playlists, supporting automated playlist recommendations and management directly from your AI workflow.
- Are there prompt templates or resources included?
No prompt templates or explicit MCP resources are provided by default. All integration relies on the available toolset and your workflow design.
Integrate Spotify with FlowHunt
Automate music playback and management in your AI flows by connecting the Spotify MCP Server to FlowHunt.