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Deepseek R1 MCP Server

by kamelirzouni
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JavaScript
Hybrid

Deepseek R1 MCP 服务器

Deepseek R1 语言模型的模型上下文协议 (MCP) 服务器实现。Deepseek R1 是一个功能强大的语言模型，针对推理任务进行了优化，其上下文窗口包含 8192 个标记。

为什么选择 Node.js？此实现使用 Node.js/TypeScript，因为它能够与 MCP 服务器提供最稳定的集成。Node.js SDK 提供了更好的类型安全性、错误处理能力以及与 Claude Desktop 的兼容性。

快速入门

手动安装

# Clone and install
git clone https://github.com/66julienmartin/MCP-server-Deepseek_R1.git
cd deepseek-r1-mcp
npm install

# Set up environment
cp .env.example .env  # Then add your API key

# Build and run
npm run build

Related MCP server: MCP Advanced Reasoning Server

先决条件

  • Node.js（v18 或更高版本）

  • npm

  • 克劳德桌面

  • Deepseek API 密钥

模型选择

本服务器默认使用deepseek-R1模型，如需使用DeepSeek-V3 ，请在src/index.ts中修改模型名称：

// For DeepSeek-R1 (default)
model: "deepseek-reasoner"

// For DeepSeek-V3
model: "deepseek-chat"

项目结构

deepseek-r1-mcp/
├── src/
│   ├── index.ts             # Main server implementation
├── build/                   # Compiled files
│   ├── index.js
├── LICENSE
├── README.md
├── package.json
├── package-lock.json
└── tsconfig.json

配置

  1. 创建.env文件：

DEEPSEEK_API_KEY=your-api-key-here

  1. 更新 Claude Desktop 配置：

{
  "mcpServers": {
    "deepseek_r1": {
      "command": "node",
      "args": ["/path/to/deepseek-r1-mcp/build/index.js"],
      "env": {
        "DEEPSEEK_API_KEY": "your-api-key"
      }
    }
  }
}

发展

npm run dev     # Watch mode
npm run build   # Build for production

特征

  • 使用 Deepseek R1 进行高级文本生成（8192 个标记上下文窗口）

  • 可配置参数（max_tokens、温度）

  • 强大的错误处理功能，提供详细的错误消息

  • 全面支持 MCP 协议

  • Claude 桌面集成

  • 支持 DeepSeek-R1 和 DeepSeek-V3 模型

API 使用

{
  "name": "deepseek_r1",
  "arguments": {
    "prompt": "Your prompt here",
    "max_tokens": 8192,    // Maximum tokens to generate
    "temperature": 0.2     // Controls randomness
  }
}

温度参数

temperature的默认值为0.2。

Deepseek 建议根据您的具体使用情况设置temperature ：

使用案例

温度

例子

编码/数学

0.0

代码生成、数学计算

数据清理/数据分析

1.0

数据处理任务

一般对话

1.3

聊天和对话

翻译

1.3

语言翻译

创意写作/诗歌

1.5

故事写作、诗歌创作

错误处理

服务器提供了常见问题的详细错误消息：

  • API 身份验证错误

  • 参数无效

  • 速率限制

  • 网络问题

贡献

欢迎贡献代码！欢迎提交 Pull 请求。

执照

麻省理工学院

Available Tools

1 tool
deepseek_r1C

Generate text using DeepSeek R1 model

ParametersJSON Schema
NameRequiredDescriptionDefault
promptYesInput text for DeepSeek
max_tokensNoMaximum tokens to generate (default: 8192)
temperatureNoSampling temperature (default: 0.2)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Generate text' implies a read/write operation that creates content, it lacks critical behavioral details such as rate limits, authentication requirements, response format, error conditions, or whether it's idempotent. The description adds minimal value beyond the basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single, clear sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it efficiently front-loaded and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a text generation tool with 3 parameters and no output schema, the description is insufficiently complete. It doesn't explain what kind of text is generated, typical use cases, limitations, or what the return value looks like. The combination of no annotations and no output schema means the description should provide more contextual information than it does.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline expectation but doesn't provide extra semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Generate text') and specifies the resource ('using DeepSeek R1 model'), which provides a specific verb+resource combination. However, since there are no sibling tools mentioned, there's no opportunity to distinguish from alternatives, preventing a perfect score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It simply states what the tool does without any usage instructions, which is insufficient for effective tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observeddeepseek_r1
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TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as text generation using the DeepSeek R1 model, leaving no ambiguity for an agent to misselect between multiple options.

Naming Consistency5/5

A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The tool name 'deepseek_r1' follows a clear pattern that matches the server name and describes its function, with no deviations or mixed conventions present.

Tool Count2/5

One tool is too few for a server's apparent scope, as it suggests minimal functionality that might not support complex workflows. While a single tool can be appropriate for very narrow purposes, this server's name implies a broader capability that a single text generation tool does not fully cover, making it feel thin and limited.

Completeness2/5

The tool surface is severely incomplete for the server's implied domain of DeepSeek R1 model interactions. It only offers text generation, lacking obvious gaps such as model configuration, parameter tuning, or other common AI model operations like embeddings or fine-tuning, which could cause agent failures in broader tasks.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

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