Direct integration of Ableton Live's Model Context Protocol (MCP) server from a web application like this one presents significant technical challenges, primarily due to browser security sandboxing and the typical local-only nature of Ableton's MCP server.

A practical implementation would likely involve a local intermediary application (e.g., a Python or Node.js script as suggested in the project proposal) that communicates with Ableton Live via MCP on one side, and exposes a web-accessible API (e.g., REST or WebSockets) for this web application to interact with on the other side.

Key Aspects from Proposal:

• Understanding MCP: Reviewing schemas and examples from the ableton-mcp repository .
• Issuing Commands: Scripting basic Ableton actions like loading sets, adding tracks, modifying tempo.
• Context Maintenance: Using LLMs (like GPT-4) for translating natural language or other inputs into MCP commands and maintaining context.

This page serves as a placeholder for future development or demonstration of such an integration. The core AI functionalities (Mood MIDI, Rhythm Accompaniment) provided in this application generate musical data that can be imported into Ableton Live, aligning with the spirit of AI-assisted music creation.