README.md•4.42 kB
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# TIDAL MCP: My Custom Picks 🌟🎧
Most music platforms offer recommendations — Daily Discovery, Top Artists, New Arrivals, etc. — but even with the state-of-the-art system, they often feel too "aggregated". I wanted something more custom and context-aware.
With TIDAL MCP, you can ask for things like:
> *"Based on my last 10 favorites, find similar tracks — but only ones from recent years."*
>
> *"Find me tracks like those in this playlist, but slower and more acoustic."*
The LLM filters and curates results using your input, finds similar tracks via TIDAL’s API, and builds new playlists directly in your account.
<a href="https://glama.ai/mcp/servers/@yuhuacheng/tidal-mcp">
<img width="400" height="200" src="https://glama.ai/mcp/servers/@yuhuacheng/tidal-mcp/badge" alt="TIDAL: My Custom Picks MCP server" />
</a>
## Features
- 🌟 **Music Recommendations**: Get personalized track recommendations based on your listening history **plus your custom criteria**.
- ၊၊||၊ **Playlist Management**: Create, view, and manage your TIDAL playlists
## Quick Start
### Prerequisites
- Python 3.10+
- [uv](https://github.com/astral-sh/uv) (Python package manager)
- TIDAL subscription
### Installation
1. Clone this repository:
```bash
git clone https://github.com/yuhuacheng/tidal-mcp.git
cd tidal-mcp
```
2. Create a virtual environment and install dependencies using uv:
```bash
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
```
3. Install the package with all dependencies from the pyproject.toml file:
```bash
uv pip install --editable .
```
This will install all dependencies defined in the pyproject.toml file and set up the project in development mode.
## MCP Client Configuration
### Claude Desktop Configuration
To add this MCP server to Claude Desktop, you need to update the MCP configuration file. Here's an example configuration:
(you can specify the port by adding an optional `env` section with the `TIDAL_MCP_PORT` environment variable)
```json
{
"mcpServers": {
"TIDAL Integration": {
"command": "/path/to/your/uv",
"env": {
"TIDAL_MCP_PORT": "5100"
},
"args": [
"run",
"--with",
"requests",
"--with",
"mcp[cli]",
"--with",
"flask",
"--with",
"tidalapi",
"mcp",
"run",
"/path/to/your/project/tidal-mcp/mcp_server/server.py"
]
}
}
}
```
Example scrrenshot of the MCP configuration in Claude Desktop:
### Steps to Install MCP Configuration
1. Open Claude Desktop
2. Go to Settings > Developer
3. Click on "Edit Config"
4. Paste the modified JSON configuration
5. Save the configuration
6. Restart Claude Desktop
## Suggested Prompt Starters
Once configured, you can interact with your TIDAL account through a LLM by asking questions like:
- *“Recommend songs like those in this playlist, but slower and more acoustic.”*
- *“Create a playlist based on my top tracks, but focused on chill, late-night vibes.”*
- *“Find songs like these in playlist XYZ but in languages other than English.”*
*💡 You can also ask the model to:*
- Use more tracks as seeds to broaden the inspiration.
- Return more recommendations if you want a longer playlist.
- Or delete a playlist if you’re not into it — no pressure!
## Available Tools
The TIDAL MCP integration provides the following tools:
- `tidal_login`: Authenticate with TIDAL through browser login flow
- `get_favorite_tracks`: Retrieve your favorite tracks from TIDAL
- `recommend_tracks`: Get personalized music recommendations
- `create_tidal_playlist`: Create a new playlist in your TIDAL account
- `get_user_playlists`: List all your playlists on TIDAL
- `get_playlist_tracks`: Retrieve all tracks from a specific playlist
- `delete_tidal_playlist`: Delete a playlist from your TIDAL account
## License
[MIT License](LICENSE)
## Acknowledgements
- [Model Context Protocol (MCP)](https://github.com/modelcontextprotocol/python-sdk)
- [TIDAL Python API](https://github.com/tamland/python-tidal)