"A service for accessing music through Apple Music" matching MCP servers:

Enables AI agents to safely access and manage a single Apple Music account, including indefinite listening history, analytics, playlists, and recommendations.

Enables MCP clients to search songs, retrieve details and lyrics, and manage personal playlists on NetEase Cloud Music, with optional local player control on macOS, all through a privacy-first, self-hosted service.

Two-mode creative music studio for AI: scored composition (ABC notation with sheet music) and live performance (Strudel live coding with TidalCycles), with interactive UI rendering inline in Claude Desktop and other MCP clients.

Enables MCP clients to query NetEase Cloud Music data such as songs, artists, albums, playlists, lyrics, and a logged-in user's library in compact, paginated, structured form, along with guarded playlist and like write operations.

Enables MCP-compatible agents to queue, run, and track local AI music generation jobs with dry-run defaults, license recording, and pluggable pipeline adapters for YuE or compatible backends.

Enables AI assistants to search for music and create/manage playlists on YouTube Music via OAuth 2.0 authentication.

Provides intelligent access to local music collections through advanced metadata management, album classification across 8 types, collection analytics, and smart search capabilities for AI-powered music library organization.

An MCP server that enables AI applications to search YouTube music videos and manage playlists via the YouTube Data API v3, with OAuth support for playlist and subscription management.

Enables AI-assisted music composition through copyable pattern templates, style constraints, and arrangement tools that compile to MIDI files. Provides 30+ tools for managing musical structures, layers, patterns, and styles with deterministic compilation from YAML arrangements.

Enables music discovery and recommendations through the free Last.fm API by exposing tools for artist and track search, similarity-based suggestions, genre or mood-based discovery, and personalized recommendations built from a Last.fm user's listening history.

Integrates Apple Music with MCP clients to search the global catalog, manage personal playlists, and access library data. It enables users to perform actions like creating playlists, adding tracks, and viewing recommendations through natural language commands.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Enables natural language control of Music Assistant home audio system, including playing music, controlling playback, adjusting volume, and managing queues, with intelligent player and provider resolution.

A server that provides QQ Music search functionality through the Modular Control Protocol, allowing users to search for music tracks by keyword and retrieve song information.

Enables AI assistants to search, play, queue, pause, resume, and skip tracks in a shared music room via stdio MCP tools, while a synchronized PWA mini/full player serves human listeners.

Enables freelancers to create, store, render, and manage service agreements with scope, deliverables, rate, termination, liability, and signature blocks, including a before-send checklist and clause library.

A production-ready generic FastMCP server template with SQLAlchemy async CRUD, enabling rapid bootstrapping of MCP data-management services. It provides registry-driven CRUD, FK resolution, conflict versioning, and multiple transports.

A production-minded RAG service for MCP that answers questions over your documents with hybrid retrieval, PII redaction, and source citations, packaged for Docker/Kubernetes.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.