Frequently Asked Questions about TIDAL MCP

Q: What is TIDAL MCP?

A: TIDAL MCP (My Custom Picks) is a tool that uses Large Language Models (LLMs) to create personalized music playlists within your TIDAL account. It allows you to filter and curate tracks based on your specific preferences, going beyond generic recommendations.

Q: What are the prerequisites for using TIDAL MCP?

A: You need Python 3.10 or higher, the uv package manager, and a TIDAL subscription.

Q: How do I install TIDAL MCP?

A: First, clone the repository from GitHub. Then, create a virtual environment and install the dependencies using uv pip install --editable .

Q: How do I configure TIDAL MCP with Claude Desktop?

A: You need to update the MCP configuration file in Claude Desktop’s settings. An example configuration is provided in the documentation, which requires specifying the path to your uv executable and the mcp_server/server.py file.

Q: What tools are available in TIDAL MCP?

A: The available tools include tidal_login (for authentication), get_favorite_tracks, recommend_tracks, create_tidal_playlist, get_user_playlists, get_playlist_tracks, and delete_tidal_playlist.

Q: Can I use TIDAL MCP to delete playlists?

A: Yes, the delete_tidal_playlist tool allows you to delete playlists directly from your TIDAL account.

Q: How does TIDAL MCP differ from standard music recommendations?

A: TIDAL MCP uses LLMs to understand and incorporate your custom criteria, providing much more personalized and nuanced recommendations compared to typical aggregated data-driven suggestions.

Q: Is TIDAL MCP free to use?

A: TIDAL MCP is an open-source project. However, you need a TIDAL subscription to use it effectively, as it interacts with your TIDAL account.

Q: What kind of prompts can I use to get the best results?

A: Experiment with prompts like “Recommend songs like those in this playlist, but slower and more acoustic,” or “Create a playlist based on my top tracks, but focused on chill, late-night vibes.”

Q: Where can I find more information about the Model Context Protocol (MCP)?

A: You can find more information about MCP on the official GitHub repository: https://github.com/modelcontextprotocol/python-sdk.

Q: How can UBOS help with AI Agent development?

A: UBOS is a full-stack AI Agent development platform that helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems, allowing you to create engaging and personalized experiences for your users.