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Deepseek Fr Mcp Server

Deepseek Fr Mcp Server

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deepseekfr.orgAI & Agents0Updated 23w ago

About Deepseek Fr Mcp Server

Deepseek Fr Mcp Server exposes DeepSeek FR’s models, prompts, and chat workflow information to MCP-compatible clients. It is a read-only reference server for users evaluating the French-language service.

Key features

  1. 01Model and capability listings
  2. 02Pricing and official links
  3. 03FAQ and site resources
  4. 04Chat evaluation prompts

Use cases

  1. 01Checking available models before evaluation
  2. 02Looking up pricing or support links

MCP support

The MCP server exposes tools, resources, and prompts describing DeepSeek FR to compatible clients. It does not provide model inference.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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
npx -y @smithery/cli install deepseekfr-mcp --client claude

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

Install from source
git clone https://github.com/rocnubie/deepseekfr-mcp.git
cd deepseekfr-mcp
pnpm install

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

{
  "mcpServers": {
    "deepseekfr-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/deepseekfr-mcp/src/index.mjs"
      ]
    }
  }
}
Debug with MCP Inspector
npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.