DeepSeek FR MCP

io.github.rocnubie由 GitHub 帳號 rocnubie 發布v0.1.0更新於 Oct 24, 2026

Independent French workspace for evaluating DeepSeek-V3-class chat and DeepSeek-R1 reasoning.

已驗證STDIO僅桌面知識與記憶AI 與機器學習

概覽

AI 產生的概覽

一個唯讀的本機 MCP 伺服器,為助理提供法語 DeepSeek FR 聊天網站的參考資訊:模型、價格、常見問題與官方連結。

可以做什麼
列出網站提供的聊天模型,並附能力說明,以及 README 中描述的模型等級與推理模式。取得官方價格入口。取得官方連結(網站、支援、可用時的文件)。讀取網站資源,涵蓋模型、價格、簡短常見問題與標準網址。使用內建提示詞概述該網站,或以預設設定開始一次聊天評估工作階段。
適用情境
當使用者希望助理說明 DeepSeek FR 是什麼、提供哪些模型、價格與官方連結在哪裡,或草擬一次法語聊天評估工作階段,而不必離開 MCP 用戶端時適用。
執行需求
以本機程序透過 stdio 執行,需用 Node.js 啟動(例如以 node 執行伺服器進入點檔案),或透過 Smithery CLI 安裝。未宣告需要 API 金鑰、帳號或環境變數。
安裝前請注意
此伺服器為唯讀,只回傳關於網站的參考文字,本身不呼叫模型也不進行聊天。README 是網站營運方的宣傳材料,其中的模型、價格與基準測試說法應視為未經查證。透過 Smithery CLI 或從原始碼安裝會把第三方程式碼下載到本機。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 DeepSeek FR MCP,將其新增到工作區。
  2. 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

DeepSeek FR MCP Server

DeepSeek FR | DeepSeek V3 & R1 workflows in French

[MCP Badge] [smithery] [Stdio Transport] [Read Only] [MCP] [License: MIT] [Zero Config]

A Model Context Protocol server that exposes the canonical DeepSeek FR 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://deepseekfr.org

💬 About DeepSeek FR

DeepSeek FR is a French-localized chat interface built around DeepSeek's latest AI models, offering French-speaking users direct access to a capable large language model without needing to navigate an English-first platform. The site provides two model variants — a Pro version aimed at complex reasoning and advanced code tasks, and a Flash version tuned for faster everyday responses — both sharing a one-million-token context window. Users interact through a clean chat interface that supports adjustable reasoning depth, making it practical for everything from quick questions to demanding multi-step analysis. The platform also documents API compatibility with OpenAI and Anthropic conventions, lowering the barrier for developers already familiar with those ecosystems.

Key Features

  • Two model tiers: Pro for deep reasoning and code-heavy work; Flash for lower-latency, everyday use — both with a 1M token context window.
  • Three reasoning modes: Non-think (maximum speed), Think High (balanced precision), and Think Max (deepest analysis), selectable per conversation.
  • Extended context handling: Processes long documents such as contracts, research papers, and technical manuals in a single session without chunking.
  • API compatibility: Works with OpenAI- and Anthropic-style API clients, so existing tooling can connect with minimal changes.
  • Benchmark transparency: The site publishes performance data across knowledge, reasoning, code, math, and agent workflow benchmarks so users can evaluate fit before integrating.
  • Local execution support: Documentation covers running models locally with encoding specifications for teams that prefer on-premise deployments.

Use Cases

  • Document review: Feeding long contracts, compliance documents, or technical manuals into the chat to extract summaries, flag inconsistencies, or answer specific questions.
  • Code assistance: Reviewing, debugging, or refactoring code across common languages, with the Pro model handling complex architectural questions.
  • Research and reasoning: Working through multi-step analytical problems — scientific literature, legal arguments, or financial modeling — where depth matters more than speed.
  • Content drafting: Generating French-language copy, reports, or structured documents for professional or editorial use.
  • API prototyping: Testing DeepSeek model responses through a familiar chat interface before wiring them into an application via the compatible API.

Who Is It For

DeepSeek FR is aimed primarily at French-speaking professionals and developers who want a capable AI assistant without switching to an English-language interface. Developers benefit from the API compatibility and local execution options; researchers and analysts value the long context window and adjustable reasoning depth; writers and content teams find the French-native interface reduces friction in day-to-day drafting tasks. The dual-model approach also makes it accessible to non-technical users who need quick answers as well as to technical teams running sustained, resource-intensive workflows — without requiring them to choose a single tool for both.

Tools

list_models

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

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for DeepSeek FR.

Input: no parameters. Returns: text/markdown.

get_official_links

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

Input: no parameters. Returns: text/markdown.

Resources

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

Prompts

tell_me_about_deepseekfr

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

start_chat_session_deepseekfr

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

Installation

Install via Smithery

bash
npx -y @smithery/cli install deepseekfr-mcp --client claude

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

Install from source

bash
git clone https://github.com/rocnubie/deepseekfr-mcp.gitcd deepseekfr-mcppnpm install

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

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

Debug with MCP Inspector

bash
npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

bash
pnpm installpnpm start                 # run the server over stdio

License

MIT

來源:README.md,提交 111a49c

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

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