Qwen MCP
io.github.rocnubie由 GitHub 帳號 rocnubie 發布v0.1.0更新於 Oct 24, 2026
Qwen AI Chat guide to Qwen3.6-Plus and qwen3.6-flash with practical notes on 1M context, coding
概覽
一個唯讀的本機 MCP 伺服器,為助理提供 Qwen 聊天模型、價格、常見問題與官方連結的參考資訊。
- 可以做什麼
- 列出站點提供的聊天模型與能力說明
- 回傳標準的價格入口
- 回傳官網、支援與文件等官方連結
- 提供模型、價格、FAQ 與連結的靜態資源
- 提供概述站點與開啟聊天評估工作階段的提示詞
- 適用情境
- 適合需要助理在對話中回答 Qwen 聊天模型、上下文長度、價格入口或官方連結等問題時使用。它只是小型參考資料,並不能真正呼叫 Qwen 模型。
- 執行需求
- 以本機 stdio 程序執行,需用 Node.js 啟動;README 提供透過 Smithery CLI 或從原始碼以 pnpm 安裝的方式。未宣告需要 API 金鑰、帳號或環境變數。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Qwen MCP,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Qwen MCP Server
Qwen AI Chat Guide for Qwen3.6-Plus, Flash, and 1M Context
[MCP Badge] [License: MIT] [Zero Config] [Node] [MCP] [smithery]
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
(Replace claude with cursor, windsurf, or continue for those clients.)
Install from source
Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):
Debug with MCP Inspector
Official Links
- Website: https://qwenchat.online
- Pricing: https://qwenchat.online/pricing
- GitHub: https://github.com/Rocniubi/MSA
- Support: [email protected]
Development
License
MIT
來源:README.md,提交 2e3f391
工具
0版本歷史
1- v0.1.0最新Sep 16, 2026
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