What are the prerequisites to run spotify_mcp?
You need a Spotify Developer account with a registered application, a redirect URI (typically `http://localhost:8888/callback`), and Python with a virtual environment.
@jmoro0408
基本信息
MCP Server to control Spotify
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"spotify_mcp": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
spotify_mcp is a Spotify integration built using the Model Context Protocol (MCP). It provides tools and resources for interacting with the Spotify API, enabling control over playback and access to user data through the MCP framework.
Clone the repository, set up a virtual environment, install dependencies with uv sync, configure Spotify API credentials in a .env file, and run python src/server.py. For use with Claude as an MCP client, edit claude_desktop_config.json to include the server configuration with your Spotify credentials.
You need a Spotify Developer account with a registered application, a redirect URI (typically `http://localhost:8888/callback`), and Python with a virtual environment.
You must set the environment variables `SPOTIPY_CLIENT_ID`, `SPOTIPY_CLIENT_SECRET`, and `SPOTIPY_REDIRECT_URI` in a `.env` file or in the MCP client configuration.
The README specifies running an MCP server via `python src/server.py`. Integration with clients like Claude uses standard MCP configuration (stdio transport).
Currently, adding songs to a playlist, adding tracks, and creating playlists are listed as “To Implement” and are not yet supported.
It accesses playback state (current song, queue), user playlists, liked songs, recently played tracks, and listening history (most played songs by period).
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