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TIDAL MCP: My Custom Picks

README.md
![tidal-mcp-main](./public/3.png)
<p align="center"><em>Hosted by Modl, any commits or changes made by the Modl team is to ensure compatibility</em></p>

# TIDAL MCP: My Custom Picks 🌟🎧

![Demo: Music Recommendations in Action](./assets/tidal_mcp_demo.gif)

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:
![Claude MCP Configuration](./assets/claude_desktop_config.png)

### 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)

TDQS

A4.3/5.0

Scored across 7 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: create_tidal_playlist and delete_tidal_playlist handle playlist lifecycle, get_favorite_tracks and get_playlist_tracks retrieve different track sources, get_user_playlists lists playlists, recommend_tracks provides recommendations, and tidal_login handles authentication. The descriptions reinforce these distinct roles, making misselection unlikely.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case: create_tidal_playlist, delete_tidal_playlist, get_favorite_tracks, get_playlist_tracks, get_user_playlists, recommend_tracks, and tidal_login. The naming is predictable and readable throughout the set, with no deviations in style or convention.

Tool Count5/5

With 7 tools, the count is well-scoped for managing TIDAL playlists and tracks. Each tool earns its place by covering essential operations like authentication, playlist CRUD, track retrieval, and recommendations, without being overly sparse or bloated for the domain.

Completeness4/5

The tool set provides strong coverage for playlist management (create, delete, list, view tracks) and track operations (favorites, recommendations), with authentication included. A minor gap exists in updating existing playlists (e.g., add/remove tracks or edit metadata), but agents can work around this by recreating playlists as needed.

Maintenance

ActivityInactive
ResponsivenessNo issues