MCP Servers

qBittorrent MCP

A service that provides programmatic access to qBittorrent's WebUI API, enabling management of torrents, trackers, tags, speed controls, and system information through natural language.

README

qBittorrent MCP 服务

qBittorrent MCP 是一个基于 FastMCP 的服务，提供了与 qBittorrent WebUI API 交互的功能接口。

功能列表

该服务提供了以下功能：

种子管理

add_torrent: 添加种子文件到 qBittorrent
delete_torrent: 删除指定种子（可选同时删除文件）
pause_torrent: 暂停种子下载
resume_torrent: 恢复种子下载
get_torrent_list: 获取所有种子列表

跟踪器与标签

get_torrent_trackers: 获取种子的跟踪器列表
add_trackers_to_torrent: 向种子添加新的跟踪器
add_torrent_tags: 为种子添加标签

速度与优先级控制

set_global_download_limit: 设置全局下载速度限制
set_global_upload_limit: 设置全局上传速度限制
set_torrent_download_limit: 设置特定种子的下载速度限制
set_torrent_upload_limit: 设置特定种子的上传速度限制
set_file_priority: 设置特定文件的下载优先级

系统信息

get_application_version: 获取qBittorrent应用程序版本

配置

服务使用以下配置参数：

DEFAULT_HOST: qBittorrent WebUI的主机地址
DEFAULT_USERNAME: qBittorrent WebUI用户名
DEFAULT_PASSWORD: qBittorrent WebUI密码

使用方法

确保已安装所需依赖：
```
pip install httpx mcp
```
运行MCP服务：
```
python main.py
```

开发

服务分为两个主要文件：

main.py: 定义MCP服务接口和配置参数
api.py: 实现与qBittorrent WebUI的交互逻辑

   "mcp_servers": [
        {
            "command": "uv",
            "args": [
                "--directory",
                "/workspace/PC-Canary/apps/qBittorrent/qbittorrent_mcp",
                "run",
                "qbittorrent.py"
            ]
        }
    ]

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official

Featured

TypeScript

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official

Featured

Local

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official

Featured

TypeScript

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official

Featured

Python

E2B

Using MCP to run code via e2b.

Official

Featured

Neon Database

MCP server for interacting with Neon Management API and databases

Official

Featured

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official

Featured

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official

Featured