https://github.com/aserper/jellyseerr-mcp
An MCP server for jellyseerr
https://github.com/aserper/jellyseerr-mcp
Last synced: 3 months ago
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An MCP server for jellyseerr
- Host: GitHub
- URL: https://github.com/aserper/jellyseerr-mcp
- Owner: aserper
- Created: 2025-08-21T05:29:16.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-12-12T01:49:51.000Z (7 months ago)
- Last Synced: 2025-12-23T14:43:10.956Z (6 months ago)
- Language: Python
- Size: 2.4 MB
- Stars: 2
- Watchers: 0
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Jellyseerr MCP Server
[](https://github.com/aserper/jellyseerr-mcp/actions/workflows/test.yml)
[](https://www.python.org/downloads/)
[](README.md#license)
[](https://github.com/aserper/jellyseerr-mcp/pkgs/container/jellyseerr-mcp)
[](https://github.com/aserper/jellyseerr-mcp)
[](https://github.com/aserper/jellyseerr-mcp/fork)
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
## 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.
```
JELLYSEERR_URL=https://your-jellyseerr.example.com
JELLYSEERR_API_KEY=your_api_key_here
JELLYSEERR_TIMEOUT=15
```
## Running the MCP server
```
python -m jellyseerr_mcp
```
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
```bash
docker pull ghcr.io/aserper/jellyseerr-mcp:latest
```
### Build Locally
```bash
docker build -t jellyseerr-mcp .
```
### Run
```bash
# If you pulled from GHCR:
docker run --rm -it \
-e JELLYSEERR_URL="https://your-jellyseerr.com" \
-e JELLYSEERR_API_KEY="your_api_key" \
ghcr.io/aserper/jellyseerr-mcp:latest
# If you built locally:
docker run --rm -it \
-e JELLYSEERR_URL="https://your-jellyseerr.com" \
-e JELLYSEERR_API_KEY="your_api_key" \
jellyseerr-mcp
```
### Multi-MCP Configuration
The server is designed to work seamlessly with multi-mcp configurations. Example `mcp.json`:
```json
{
"mcpServers": {
"jellyseerr": {
"command": "/path/to/.venv/bin/python",
"args": ["-m", "jellyseerr_mcp"],
"env": {
"JELLYSEERR_URL": "https://your-jellyseerr.example.com",
"JELLYSEERR_API_KEY": "your_api_key_here"
}
}
}
}
```
## 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`.