Skip to main content

AI agent for qBittorrent management, RSS automation, and search.

Project description

qBittorrent Manager - A2A | AG-UI | MCP

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub

GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues

GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 0.8.0

Overview

qBittorrent Manager MCP Server + A2A Agent

AI agent for qBittorrent management, RSS automation, and search.

This repository is actively maintained - Contributions are welcome!

MCP

Using as an MCP Server

The MCP Server can be run in two modes: stdio (for local testing) or http (for networked access).

Environment Variables

  • QBITTORRENT_URL: The URL of the target service.
  • QBITTORRENT_PASSWORD: The API token or access token.

Run in stdio mode (default):

export QBITTORRENT_URL="http://localhost:8080"
export QBITTORRENT_PASSWORD="your_token"
qbittorrent-mcp --transport "stdio"

Run in HTTP mode:

export QBITTORRENT_URL="http://localhost:8080"
export QBITTORRENT_PASSWORD="your_token"
qbittorrent-mcp --transport "http" --host "0.0.0.0" --port "8000"

A2A Agent

Run A2A Server

export QBITTORRENT_URL="http://localhost:8080"
export QBITTORRENT_PASSWORD="your_token"
qbittorrent-agent --provider openai --model-id gpt-4o --api-key sk-...

Docker

Build

docker build -t qbittorrent-agent .

Run MCP Server

docker run -d \
  --name qbittorrent-agent \
  -p 8000:8000 \
  -e TRANSPORT=http \
  -e QBITTORRENT_URL="http://your-service:8080" \
  -e QBITTORRENT_PASSWORD="your_token" \
  knucklessg1/qbittorrent-agent:latest

Deploy with Docker Compose

services:
  qbittorrent-agent:
    image: knucklessg1/qbittorrent-agent:latest
    environment:
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=http
      - QBITTORRENT_URL=http://your-service:8080
      - QBITTORRENT_PASSWORD=your_token
    ports:
      - 8000:8000

Configure mcp.json for AI Integration (e.g. Claude Desktop)

{
  "mcpServers": {
    "qbittorrent": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "qbittorrent-agent",
        "qbittorrent-mcp"
      ],
      "env": {
        "QBITTORRENT_URL": "http://your-service:8080",
        "QBITTORRENT_PASSWORD": "your_token"
      }
    }
  }
}

Install Python Package

python -m pip install qbittorrent-agent
uv pip install qbittorrent-agent

Repository Owners

GitHub followers GitHub User's stars

MCP Configuration Examples

1. Standard IO (stdio) Deployment

{
  "mcpServers": {
    "qbittorrent-agent": {
      "command": "uv",
      "args": [
        "run",
        "qbittorrent-mcp"
      ],
      "env": {
        "AGENT_DESCRIPTION": "<YOUR_AGENT_DESCRIPTION>",
        "AGENT_SYSTEM_PROMPT": "<YOUR_AGENT_SYSTEM_PROMPT>",
        "DEFAULT_AGENT_NAME": "<YOUR_DEFAULT_AGENT_NAME>",
        "QBITTORRENT_AGENT_VERIFY": "<YOUR_QBITTORRENT_AGENT_VERIFY>",
        "QBITTORRENT_PASSWORD": "<YOUR_QBITTORRENT_PASSWORD>",
        "QBITTORRENT_URL": "<YOUR_QBITTORRENT_URL>",
        "QBITTORRENT_USERNAME": "<YOUR_QBITTORRENT_USERNAME>"
      }
    }
  }
}

2. Streamable HTTP (SSE) Deployment

{
  "mcpServers": {
    "qbittorrent-agent": {
      "command": "uv",
      "args": [
        "run",
        "qbittorrent-mcp",
        "--transport",
        "http",
        "--host",
        "0.0.0.0",
        "--port",
        "8000"
      ],
      "env": {
        "AGENT_DESCRIPTION": "<YOUR_AGENT_DESCRIPTION>",
        "AGENT_SYSTEM_PROMPT": "<YOUR_AGENT_SYSTEM_PROMPT>",
        "DEFAULT_AGENT_NAME": "<YOUR_DEFAULT_AGENT_NAME>",
        "QBITTORRENT_AGENT_VERIFY": "<YOUR_QBITTORRENT_AGENT_VERIFY>",
        "QBITTORRENT_PASSWORD": "<YOUR_QBITTORRENT_PASSWORD>",
        "QBITTORRENT_URL": "<YOUR_QBITTORRENT_URL>",
        "QBITTORRENT_USERNAME": "<YOUR_QBITTORRENT_USERNAME>"
      }
    }
  }
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qbittorrent_agent-0.8.0.tar.gz (23.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

qbittorrent_agent-0.8.0-py3-none-any.whl (25.4 kB view details)

Uploaded Python 3

File details

Details for the file qbittorrent_agent-0.8.0.tar.gz.

File metadata

  • Download URL: qbittorrent_agent-0.8.0.tar.gz
  • Upload date:
  • Size: 23.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for qbittorrent_agent-0.8.0.tar.gz
Algorithm Hash digest
SHA256 3c4c5899e5d59ee32a88848cc51301a57ac678d7e0af3d726e8ffb3b741949bd
MD5 c747861ace7e6b4303028a2486cc84d7
BLAKE2b-256 b76e5475c234bedc420a170744998e879f33f74e64cd3e446f8537208a8b8224

See more details on using hashes here.

File details

Details for the file qbittorrent_agent-0.8.0-py3-none-any.whl.

File metadata

File hashes

Hashes for qbittorrent_agent-0.8.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f2d82f2bde600724984016cca1f7624ad7834a2b3a378c9a4098e2d6d8cc7160
MD5 ac35ace0415a9641d45f37e3db870a7c
BLAKE2b-256 9a2c2db875da0aaa274032ede0dc32a83426602b125a54727f9946e2bcd67232

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page