DeepSeek MCP Server


A Model Context Protocol (MCP) server that integrates DeepSeek AI models with MCP-compatible clients. Access DeepSeek's powerful chat and reasoning models directly from your development environment.

Compatible with:
- Claude Code CLI
- Gemini CLI (if MCP support is available)
- Any MCP-compatible client

> Note: This is an unofficial community project and is not affiliated with DeepSeek.

Quick Start

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``bash


Install and configure with API key (available in all projects)

claude mcp add -s user deepseek npx @arikusi/deepseek-mcp-server -e DEEPSEEK_API_KEY=your-key-here

Or install for current project only

claude mcp add deepseek npx @arikusi/deepseek-mcp-server -e DEEPSEEK_API_KEY=your-key-here
`

Scope options:
- -s user: Available in all your projects (recommended)
- -s local: Only in current project (default)
- -s project: Project-specific .mcp.json file

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`bash


Install and configure with API key


gemini mcp add deepseek npx @arikusi/deepseek-mcp-server -e DEEPSEEK_API_KEY=your-key-here
`

Get your API key: https://platform.deepseek.com

That's it! Your MCP client can now use DeepSeek models!

---

Features

- DeepSeek Chat: Fast and capable general-purpose model
- DeepSeek Reasoner (R1): Advanced reasoning with chain-of-thought explanations
- Function Calling: OpenAI-compatible tool use with up to 128 tool definitions
- Cost Tracking: Automatic cost calculation for every request (USD)
- Configurable: Environment-based configuration with validation
- 12 Prompt Templates: Pre-built templates for debugging, code review, function calling, and more
- Streaming Support: Real-time response generation
- Tested: 85 tests with 80%+ code coverage
- Type-Safe: Full TypeScript implementation
- MCP Compatible: Works with any MCP-compatible CLI (Claude Code, Gemini CLI, etc.)

Installation

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- Node.js 18+
- A DeepSeek API key (get one at https://platform.deepseek.com)

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If you prefer to install manually:

`bash
npm install -g @arikusi/deepseek-mcp-server
`

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1. Clone the repository

`bash
git clone https://github.com/arikusi/deepseek-mcp-server.git
cd deepseek-mcp-server
`

2. Install dependencies

`bash
npm install
`

3. Build the project

`bash
npm run build
`

Usage

Once configured, your MCP client will have access to the deepseek_chat tool and can use DeepSeek models.

Example prompts:
`
"Use DeepSeek to explain quantum computing"
"Ask DeepSeek Reasoner to solve: If I have 10 apples and buy 5 more..."
`

Your MCP client will automatically call the deepseek_chat tool.

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If your MCP client doesn't support the add command, manually add to your config file:

`json
{
"mcpServers": {
"deepseek": {
"command": "npx",
"args": ["@arikusi/deepseek-mcp-server"],
"env": {
"DEEPSEEK_API_KEY": "your-api-key-here"
}
}
}
}
`

Config file locations:
- Claude Code: ~/.claude.json (add to projects["your-project-path"].mcpServers section)
- Other MCP clients: Check your client's documentation for config file location

Available Tools

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Chat with DeepSeek AI models with automatic cost tracking and function calling support.

Parameters:

- messages (required): Array of conversation messages
- role: "system" | "user" | "assistant" | "tool"
- content: Message text
- tool_call_id (optional): Required for tool role messages
- model (optional): "deepseek-chat" (default) or "deepseek-reasoner"
- temperature (optional): 0-2, controls randomness (default: 1.0)
- max_tokens (optional): Maximum tokens to generate
- stream (optional): Enable streaming mode (default: false)
- tools (optional): Array of tool definitions for function calling (max 128)
- tool_choice (optional): "auto" | "none" | "required" | {type: "function", function: {name: "..."}}

Response includes:
- Content with formatting
- Function call results (if tools were used)
- Request information (tokens, model, cost in USD)
- Structured data with cost_usd and tool_calls fields

Example:

`json
{
"messages": [
{
"role": "user",
"content": "Explain the theory of relativity in simple terms"
}
],
"model": "deepseek-chat",
"temperature": 0.7,
"max_tokens": 1000
}
`

DeepSeek Reasoner Example:

`json
{
"messages": [
{
"role": "user",
"content": "If I have 10 apples and eat 3, then buy 5 more, how many do I have?"
}
],
"model": "deepseek-reasoner"
}
`

The reasoner model will show its thinking process in tags followed by the final answer.

Function Calling Example:

`json
{
"messages": [
{
"role": "user",
"content": "What's the weather in Istanbul?"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name"
}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}
`

When the model decides to call a function, the response includes tool_calls with the function name and arguments. You can then send the result back using a tool role message with the matching tool_call_id.

Available Prompts

Pre-built prompt templates for common tasks (12 total):

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- debug_with_reasoning: Debug code with step-by-step analysis
- code_review_deep: Comprehensive code review (security, performance, quality)
- research_synthesis: Research topics and create structured reports
- strategic_planning: Create strategic plans with reasoning
- explain_like_im_five: Explain complex topics in simple terms

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- mathematical_proof: Prove mathematical statements rigorously
- argument_validation: Analyze arguments for logical fallacies
- creative_ideation: Generate creative ideas with feasibility analysis
- cost_comparison: Compare LLM costs for tasks
- pair_programming: Interactive coding with explanations

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- function_call_debug: Debug function calling issues with tool definitions and messages
- create_function_schema: Generate JSON Schema for function calling from natural language

Each prompt is optimized for the DeepSeek Reasoner model to provide detailed reasoning.

Models

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- Best for: General conversations, coding, content generation
- Speed: Fast
- Context: 64K tokens
- Cost: Most economical

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- Best for: Complex reasoning, math, logic problems, multi-step tasks
- Speed: Slower (shows thinking process)
- Context: 64K tokens
- Special: Provides chain-of-thought reasoning
- Output: Both reasoning process and final answer

Configuration

The server is configured via environment variables. All settings except DEEPSEEK_API_KEY are optional.

| Variable | Default | Description |
|----------|---------|-------------|
| DEEPSEEK_API_KEY | (required) | Your DeepSeek API key |
| DEEPSEEK_BASE_URL | https://api.deepseek.com | Custom API endpoint |
| SHOW_COST_INFO | true | Show cost info in responses |
| REQUEST_TIMEOUT | 60000 | Request timeout in milliseconds |
| MAX_RETRIES | 2 | Maximum retry count for failed requests |

Example with custom config:
`bash
claude mcp add -s user deepseek npx @arikusi/deepseek-mcp-server \
-e DEEPSEEK_API_KEY=your-key \
-e SHOW_COST_INFO=false \
-e REQUEST_TIMEOUT=30000
`

Development

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`
deepseek-mcp-server/
├── src/
│ ├── index.ts # Main MCP server, tool & prompt registration
│ ├── deepseek-client.ts # DeepSeek API wrapper (OpenAI SDK)
│ ├── config.ts # Centralized config with Zod validation
│ ├── cost.ts # Cost calculation and formatting
│ ├── schemas.ts # Zod input validation schemas
│ ├── types.ts # TypeScript type definitions
│ ├── config.test.ts # Config tests
│ ├── cost.test.ts # Cost tests
│ ├── schemas.test.ts # Schema validation tests
│ ├── deepseek-client.test.ts # Client tests
│ └── function-calling.test.ts # Function calling tests
├── dist/ # Compiled JavaScript
├── vitest.config.ts # Test configuration
├── package.json
├── tsconfig.json
└── README.md
`

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`bash
npm run build
`

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`bash
npm run watch
`

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`bash


Run all tests

npm test

Watch mode

npm run test:watch

With coverage report

npm run test:coverage
`

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`bash


Set API key

export DEEPSEEK_API_KEY="your-key"

Run the server

npm start
`

The server will start and wait for MCP client connections via stdio.

Troubleshooting

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Option 1: Use the correct installation command
`bash


Make sure to include -e flag with your API key


claude mcp add deepseek npx @arikusi/deepseek-mcp-server -e DEEPSEEK_API_KEY=your-key-here
`

Option 2: Manually edit the config file

If you already installed without the API key, edit your config file:

1. For Claude Code: Open ~/.claude.json (Windows: C:\Users\USERNAME\.claude.json)
2. Find the "mcpServers" section under your project path
3. Add the env field with your API key:
`json
"deepseek": {
"type": "stdio",
"command": "npx",
"args": ["@arikusi/deepseek-mcp-server"],
"env": {
"DEEPSEEK_API_KEY": "your-api-key-here"
}
}
`
4. Save and restart Claude Code

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1. Check your API key is valid
2. Verify you have internet connection
3. Check DeepSeek API status at https://status.deepseek.com

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1. Verify the path to dist/index.js is correct
2. Make sure you ran npm run build
3. Check your MCP client's logs for errors
4. Restart your MCP client completely

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Make the file executable:

`bash
chmod +x dist/index.js
`

Publishing to npm

To share this MCP server with others:

1. Run npm login
2. Run npm publish --access public

Users can then install with:

`bash
npm install -g @arikusi/deepseek-mcp-server
`

Contributing

Contributions are welcome! Please read our Contributing Guidelines before submitting PRs.

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Found a bug or have a feature request? Please open an issue using our templates.

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`bash


Clone the repo

git clone https://github.com/arikusi/deepseek-mcp-server.git
cd deepseek-mcp-server

Install dependencies

npm install

Build in watch mode

npm run watch

Run tests

npm test

Lint

npm run lint
``

Changelog

See CHANGELOG.md for version history and updates.

License

MIT License - see LICENSE file for details

Support

- Documentation
- Bug Reports
- Discussions
- Contact: GitHub Issues

Resources

- DeepSeek Platform - Get your API key
- Model Context Protocol - MCP specification
- DeepSeek API Documentation - API reference

Acknowledgments

- Built with Model Context Protocol SDK
- Uses OpenAI SDK for API compatibility
- Created for the MCP community

---

Made by @arikusi

This is an unofficial community project and is not affiliated with DeepSeek.