Jellyseerr MCP Server

An MCP (Model Context Protocol) server for Jellyseerr that exposes Jellyseerr API functionality as MCP tools usable by LLM clients. It includes colorful, emoji-forward logging and clear console output.

Features

• Exposes key Jellyseerr endpoints as MCP tools (search, request, get request status, etc.)

• Synchronous HTTP client with robust error handling and timeouts

• Colorful, structured logging via Rich with emoji indicators

• Configuration via environment variables (.env supported)

• Non-blocking stdio server compatible with multi-mcp configurations

Related MCP server: Jira MCP Server

Requirements

• Python 3.10+

• Packages in requirements.txt

Setup

1. Create and activate a virtualenv.

2. pip install -r requirements.txt

3. Copy .env.example to .env and set your values.

Running the MCP server

You should see colorful logs indicating the server is ready on stdio. The server communicates via stdin/stdout, making it compatible with Claude Desktop and other MCP clients.

Docker

You can run the server using Docker by either pulling the pre-built image from the GitHub Container Registry (GHCR) or building it yourself.

Pull from GHCR

Build Locally

Run

Multi-MCP Configuration

The server is designed to work seamlessly with multi-mcp configurations. Example mcp.json:

Exposed tools (initial set)

• search_media(query: str) — Search Jellyseerr for media by query.

• request_media(media_id: int, media_type: str) — Create a media request.

• get_request(request_id: int) — Fetch a request’s details/status.

• ping() — Liveness check with server/transport info.

More tools can be added easily — see jellyseerr_mcp/server.py.