Provides Emby server control for LLM clients via MCP, including library management, search, playlists, and playback control.
Configuration
View docs{
"mcpServers": {
"angeltek-emby.mcp": {
"command": "uv",
"args": [
"run",
"emby_mcp_server.py"
],
"env": {
"EMBY_PASSWORD": "pass",
"EMBY_USERNAME": "user",
"LLM_MAX_ITEMS": "100",
"EMBY_SERVER_URL": "http://localhost:8096",
"EMBY_VERIFY_SSL": "True"
}
}
}
}Emby.MCP lets you connect your Emby media server to an AI client that can control playback, manage libraries, create playlists, and perform library searches through a Model Context Protocol (MCP). It gives you an “Alexa-like” interface for your personal media collection, enabling natural language commands to drive Emby actions from an MCP-compatible LLM.
To start using Emby.MCP, first ensure your MCP client (for example Claude Desktop or VS Code with MCP support) is configured to talk to the Emby.MCP server running on your machine. Begin by selecting a library to focus your conversations on, which helps narrow searches and reduces returned data. For example, in your chat with the LLM you can say: select Music library. Then you can ask to list genres, search by genre or title, manage playlists, or control playback on any known Emby player. The LLM will call the available MCP tools to log in, fetch libraries, search content, manage playlists, list players, and control playback as needed. If your request involves lyrics or long descriptions, expect the data to be chunked into manageable pieces to fit the LLM’s input limits.
Begin by mentioning Emby to encourage the MCP client to use the Emby.MCP tools. For example: list emby libraries. The system will respond with the libraries available on your server. You can then select a library, such as select BBC Sounds library, to constrain future searches and actions to that library. You can continue with searches, browsing, or content exploration within the chosen library.