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.
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
在 SourceWeft 中
- 開啟 儀表板中的 DeepSeek FR 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
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
(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://deepseekfr.org
- Pricing: https://deepseekfr.org/pricing
- Support: [email protected]
Development
License
MIT
來源:README.md,提交 111a49c
工具
0版本歷史
1- v0.1.0最新Sep 16, 2026
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