原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Qwen MCP

作者:rocnubie版本 0.1.0i★ –i–
注册名称io.github.rocnubie/chat-mcp

安装

概览

作者提供的说明(英文原文)

Qwen AI Chat guide to Qwen3.6-Plus and qwen3.6-flash with practical notes on 1M context, coding

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: –
  • 传输方式:
  • 分类: 聊天与邮件

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

作者没有在注册中心列出安装信息。请查看下方作者的 README。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 rocnubie 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“聊天与邮件”中的其他服务器比较i

  • 星标数多于此分类中其他 1848 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1848 个服务器的 10% 更新
  • 基础检查结果等于或优于此分类中其他 1848 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Qwen MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于6个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。

有什么可以替代它?

同一分类中有:Vexa, emailmd, MCP WhatsApp Cloud

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Vexa

Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.

作者:Vexa-ai广泛使用★ 29492个月前更新

在云端运行✓ vexa.ai

emailmd

Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.

作者:anypost正在增长↓ 5342/周★ 138532天前更新

电脑或云端✓ emailmd.dev

MCP WhatsApp Cloud

MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API

作者:codespar起步阶段↓ 63/周★ 2775个月前更新

在你的电脑上运行

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Qwen MCP Server

Qwen AI Chat Guide for Qwen3.6-Plus, Flash, and 1M Context

A Model Context Protocol server that exposes the canonical Qwen knowledge surface — models, prompts, and chat workflows, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://qwenchat.online

💬 About Qwen

Qwen Chat (qwenchat.online) is a browser-based workspace for interacting with Alibaba's Qwen3 family of language models. The site provides direct chat access alongside a structured evaluation environment where users can test model capabilities across distinct task categories — code, documents, visual inputs, and web generation — without setting up local infrastructure. It is designed for people who want to move quickly from curiosity to practical assessment: load a file, paste a prompt, and observe how the model handles real work rather than toy examples.

Key Features

  • 1M context window — carry multiple long files, research documents, or codebases in a single request without manually summarising between steps.
  • Model lane comparison — switch between Qwen3 Plus and Flash variants through the same interface to compare speed and quality tradeoffs on the same input.
  • OpenAI and Anthropic API compatibility — the underlying models expose both API surfaces, so existing tooling, SDKs, and prompt templates migrate with minimal changes.
  • Benchmark transparency — the site surfaces specific third-party scores (Terminal-Bench 2.0, OmniDocBench 1.5) rather than abstract capability claims, letting users calibrate expectations before committing to integration.
  • Multimodal input support — the chat accepts screenshots, PDFs, and diagrams, enabling visual reasoning tasks such as UI analysis, screen grounding, and document layout parsing.
  • Preset task examples — the interface ships with ready-made prompts covering code review, document analysis, and web prototyping, reducing the setup time needed to start a meaningful test.

Use Cases

  • Code and repository work — reviewing diffs, diagnosing build failures, or walking through a repository repair task using the extended context window to hold multiple files at once.
  • Long-document analysis — uploading policy documents, research papers, or technical specifications and asking structured questions without hitting context limits.
  • Visual and UI tasks — pasting screenshots for layout analysis, accessibility review, or screen grounding where the model identifies interactive elements by position.
  • Rapid web prototyping — generating functional HTML or component scaffolding from a brief description and iterating in the same session.
  • API migration evaluation — testing whether Qwen models can serve as a drop-in replacement for OpenAI or Anthropic endpoints in an existing workflow before switching production traffic.

Who Is It For

Qwen Chat is aimed primarily at developers, technical leads, and product teams who are already using language models in their day-to-day work and want to evaluate whether Qwen3 fits their stack. It suits teams that handle long documents or large codebases and need a context window beyond what standard tiers offer. It is also relevant to engineers assessing API compatibility before committing to a migration — the site provides enough structured evidence to make that call without requiring a full integration first. Individual developers building side projects or prototypes who want a capable model accessible directly from the browser will find it practical as well.

Tools

list_models

Return the canonical list of chat models exposed on the site, with capability notes. (Qwen)

_Input:_ no parameters. _Returns:_ text/markdown.

get_pricing

Return the canonical pricing entry point for Qwen.

_Input:_ no parameters. _Returns:_ text/markdown.

get_official_links

Return the canonical list of official links for Qwen (website, support, docs when available).

_Input:_ no parameters. _Returns:_ text/markdown.

Resources

  • site://chat/models — Supported chat models and capability notes.
  • site://chat/pricing — Canonical pricing entry point.
  • site://chat/faq — Short FAQ generated from public site metadata.
  • site://chat/links — Canonical URLs to share with users.

Prompts

tell_me_about_chat

Summarize what the site is, who it's for, and how it works. — Qwen

start_chat_session_chat

Open a chat-evaluation session against the site's models, with sensible defaults. — Qwen

Installation

Install via Smithery
npx -y @smithery/cli install chat-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source
git clone https://github.com/rocnubie/chat-mcp.git

cd chat-mcp pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{

"mcpServers": { "chat-mcp": { "command": "node", "args": [ "/absolute/path/to/chat-mcp/src/index.mjs" ] } } }

Debug with MCP Inspector
npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

  • Website: https://qwenchat.online
  • Pricing: https://qwenchat.online/pricing
  • GitHub: https://github.com/Rocniubi/MSA
  • Support: support@qwenchat.online

Development

pnpm install

pnpm start # run the server over stdio

License

MIT

问 PopNx