About Jellyfin MCP Server
Jellyfin MCP Server is a Jellyfin plugin for AI assistants that need to search media, manage playback and work with library content. Token scopes and Jellyfin user permissions govern each call, including separate administrator tools.
Key features
- 01Search and browse media libraries
- 02Control playback and view sessions
- 03Manage playlists and favorites
- 04Run administrator server tasks
- 05Scope- and user-based permissions
Use cases
- 01Find a film or series in a Jellyfin library
- 02Control playback on a device
- 03Update personal favorites or playlists
- 04Run library and metadata tasks as an administrator
MCP support
The plugin exposes Jellyfin tools to MCP clients over stateless Streamable HTTP at `POST /mcp`. Tokens determine available scopes, and calls run with the permissions of the associated Jellyfin user.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://{jellyfin_host}/mcpclaude mcp add --transport http aelui-jellyfin-plugin https://{jellyfin_host}/mcp{"mcpServers":{"aelui-jellyfin-plugin":{"type":"http","url":"https://{jellyfin_host}/mcp"}}}Open in Cursor{"servers":{"aelui-jellyfin-plugin":{"type":"http","url":"https://{jellyfin_host}/mcp"}}}Open in VS Code{"mcpServers":{"aelui-jellyfin-plugin":{"type":"http","url":"https://{jellyfin_host}/mcp"}}}{"mcpServers":{"aelui-jellyfin-plugin":{"serverUrl":"https://{jellyfin_host}/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://{jellyfin_host}/mcpAuth requiredTools
Details
From the project READMEJellyfin MCP Server plugin

A Jellyfin plugin that exposes your server to AI assistants through the Model Context Protocol (MCP). Assistants such as Claude can search and browse your library, see what you are watching, control playback on your devices, manage playlists and favorites, and (for administrators) run server tasks. Every call runs as the Jellyfin user who owns the access token, limited to that user's permissions and to the scopes granted to the token. The plugin has no runtime dependencies besides Jellyfin itself.
Compatibility
- Jellyfin 12.x only (compiled against 12.4.0,
targetAbi12.4.0.0). Older servers are not supported. - Built with .NET 10.
- MCP transport: Streamable HTTP, stateless,
POST /mcp. Protocol revisions 2025-11-25, 2025-06-18 and 2025-03-26. The stateless 2026-07-28 revision is not supported yet (see the roadmap). - Clients that send a static
Authorization: Bearerheader work; Claude Code is the supported client. Claude Desktop throughmcp-remoteis expected to work but is not yet verified. claude.ai web connectors need OAuth and are not supported yet.
Install in three steps
- In Jellyfin go to Dashboard > Plugins > Repositories > + and add
https://raw.githubusercontent.com/AeLui/jellyfin-plugin-mcp/main/manifest.json. - Open the Catalog, install MCP Server and restart Jellyfin.
- Open Dashboard > Plugins > MCP Server, create a token (pick the user and the scopes) and copy it. It is shown only once.
More detail, including a manual install, is in docs/installation.md.
Connect a client
Replace https://jellyfin.example.com with your server address and jmcp_... with your token.
Claude Code, with the plugin from this repository's marketplace (connects the server and adds the agent skill; it asks for the URL and the token, and keeps the token in your system's credential store):
/plugin marketplace add AeLui/jellyfin-plugin-mcp
/plugin install jellyfin-mcp@jellyfin-plugin-mcp
On Claude Code 2.1.275 or later, one step is enough: /plugin install jellyfin-mcp --marketplace AeLui/jellyfin-plugin-mcp. To change the URL or token later, run /plugin configure jellyfin-mcp@jellyfin-plugin-mcp.
Claude Code, server only:
claude mcp add --transport http jellyfin https://jellyfin.example.com/mcp \
--header "Authorization: Bearer jmcp_..."
Claude Desktop (claude_desktop_config.json; requires Node.js because it runs npx mcp-remote):
{
"mcpServers": {
"jellyfin": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://jellyfin.example.com/mcp",
"--header", "Authorization: Bearer jmcp_..."]
}
}
}
The token dialog in the plugin page generates both snippets for you. The Claude Desktop flow is expected to work but has not been verified against a live server yet.
Scopes and tools
22 tools in four scopes. A token only sees the tools its scopes allow.
| Scope | Tools | Purpose |
|---|---|---|
library | 9 | Read-only: search, browse, details, people, recent, next up, continue watching, history |
playback | 4 | List sessions, play, control playback, show a message |
manage | 4 | The user's own watch state and favorites, plus playlists the user owns or may edit |
admin | 5 | Users, scheduled tasks, library scan, metadata refresh (administrators only) |
Full reference: docs/tools.md.
Agent skill
skills/jellyfin-mcp/SKILL.md is an optional Agent Skill that teaches an assistant when and how to use these tools: getting ids before acting, picking a playback session, paging, and asking before destructive actions.
The Claude Code plugin above includes it. Other agents: copy the skills/jellyfin-mcp folder into their skills directory (for Claude Code without the plugin, ~/.claude/skills/ or .claude/skills/ in a project). If you install the plugin, remove any server you added with claude mcp add, or the tools show up twice.
Privacy
The plugin runs inside your Jellyfin server and makes no outbound connections. The Claude Code plugin connects only to the Jellyfin URL you configure. What your assistant does with the tool results is governed by the assistant's own privacy policy.
Documentation
- Installation and client setup
- Tool reference
- Security model - read this before exposing the endpoint beyond your LAN
- Architecture
- Development
- Roadmap
Support the project
The plugin is free and open source. If it is useful to you, you can support its development through GitHub Sponsors.
License
GPL-3.0, see LICENSE.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.