DeepSeek MCP Server

<a href="https://glama.ai/mcp/servers/arikusi/deepseek-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/arikusi/deepseek-mcp-server/badge" /> </a>

MCP server for DeepSeek AI models (Chat + Reasoner). Supports stdio and HTTP transports, Docker deployment, multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.

Compatible with:

• Claude Code CLI
• Gemini CLI
• Any MCP-compatible client (Cursor, Windsurf, etc.)

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

Quick Start

Remote (No Install)

Use the hosted endpoint directly — no npm install, no Node.js required. Bring your own DeepSeek API key:

Claude Code:

claude mcp add --transport http deepseek \
  https://deepseek-mcp.tahirl.com/mcp \
  --header "Authorization: Bearer YOUR_DEEPSEEK_API_KEY"

Cursor / Windsurf / VS Code:

{
  "mcpServers": {
    "deepseek": {
      "url": "https://deepseek-mcp.tahirl.com/mcp",
      "headers": {
        "Authorization": "Bearer ${DEEPSEEK_API_KEY}"
      }
    }
  }
}

Local (stdio)

Claude Code:

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

Gemini CLI:

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

Scope options (Claude Code):

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

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

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Features

• DeepSeek V3.2: Both models now run DeepSeek-V3.2 (since Sept 2025)
• Multi-Turn Sessions: Conversation context preserved across requests via session_id parameter
• Model Fallback & Circuit Breaker: Automatic fallback between models with circuit breaker protection against cascading failures
• MCP Resources: deepseek://models, deepseek://config, deepseek://usage — query model info, config, and usage stats
• Thinking Mode: Enable thinking on deepseek-chat with thinking: {type: "enabled"}
• JSON Output Mode: Structured JSON responses with json_mode: true
• Function Calling: OpenAI-compatible tool use with up to 128 tool definitions
• Cache-Aware Cost Tracking: Automatic cost calculation with cache hit/miss breakdown
• Session Management Tool: List, delete, and clear sessions via deepseek_sessions tool
• Configurable: Environment-based configuration with validation
• 12 Prompt Templates: Templates for debugging, code review, function calling, and more
• Streaming Support: Real-time response generation
• Multimodal Ready: Content part types for text + image input (enable with ENABLE_MULTIMODAL=true)
• Remote Endpoint: Hosted at deepseek-mcp.tahirl.com/mcp — BYOK (Bring Your Own Key), no install needed
• HTTP Transport: Self-hosted remote access via Streamable HTTP with TRANSPORT=http
• Docker Ready: Multi-stage Dockerfile with health checks for containerized deployment
• Tested: 253 tests with 90%+ code coverage
• Type-Safe: Full TypeScript implementation
• MCP Compatible: Works with any MCP-compatible CLI (Claude Code, Gemini CLI, etc.)

Installation

Prerequisites

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

Manual Installation

If you prefer to install manually:

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

From Source

1. Clone the repository

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

2. Install dependencies

npm install

3. Build the project

npm run build

Usage

Once configured, your MCP client will have access to deepseek_chat and deepseek_sessions tools, plus 3 MCP resources.

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.

Manual Configuration (Advanced)

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

{
  "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

deepseek_chat

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). Ignored when thinking mode is enabled.
• max_tokens (optional): Maximum tokens to generate (deepseek-chat: max 8192, deepseek-reasoner: max 65536)
• 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: "..."}}
• thinking (optional): Enable thinking mode {type: "enabled"}
• json_mode (optional): Enable JSON output mode (supported by both models)
• session_id (optional): Session ID for multi-turn conversations. Previous context is automatically prepended.

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:

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

DeepSeek Reasoner Example:

{
  "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 <thinking> tags followed by the final answer.

Function Calling Example:

{
  "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.

Thinking Mode Example:

{
  "messages": [
    {
      "role": "user",
      "content": "Analyze the time complexity of quicksort"
    }
  ],
  "model": "deepseek-chat",
  "thinking": { "type": "enabled" }
}

When thinking mode is enabled, temperature, top_p, frequency_penalty, and presence_penalty are automatically ignored.

JSON Output Mode Example:

{
  "messages": [
    {
      "role": "user",
      "content": "Return a json object with name, age, and city fields for a sample user"
    }
  ],
  "model": "deepseek-chat",
  "json_mode": true
}

JSON mode ensures the model outputs valid JSON. Include the word "json" in your prompt for best results. Supported by both deepseek-chat and deepseek-reasoner.

Multi-Turn Session Example:

{
  "messages": [
    {
      "role": "user",
      "content": "What is the capital of France?"
    }
  ],
  "session_id": "my-session-1"
}

Use the same session_id across requests to maintain conversation context. The server stores messages in memory and automatically prepends history to each request.

deepseek_sessions

Manage conversation sessions.

Parameters:

• action (required): "list" | "clear" | "delete"
• session_id (optional): Required when action is "delete"

Examples:

{"action": "list"}
{"action": "delete", "session_id": "my-session-1"}
{"action": "clear"}

Available Resources

MCP Resources provide read-only data about the server:

Resource URI	Description
deepseek://models	Available models with capabilities, context limits, and pricing
deepseek://config	Current server configuration (API key masked)
deepseek://usage	Real-time usage statistics (requests, tokens, costs, sessions)

Model Fallback & Circuit Breaker

When a model fails with a retryable error (429, 503, timeout), the server automatically falls back to the other model:

• deepseek-chat fails → tries deepseek-reasoner
• deepseek-reasoner fails → tries deepseek-chat

The circuit breaker protects against cascading failures:

• After CIRCUIT_BREAKER_THRESHOLD consecutive failures (default: 5), the circuit opens (fast-fail mode)
• After CIRCUIT_BREAKER_RESET_TIMEOUT ms (default: 30000), it enters half-open state and sends a probe request
• If the probe succeeds, the circuit closes and normal operation resumes

Fallback can be disabled with FALLBACK_ENABLED=false.

Available Prompts

Prompt templates (12 total):

Core Reasoning

• 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

Advanced

• 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

Function Calling

• 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

Both models run DeepSeek-V3.2 with unified pricing.

deepseek-chat

• Best for: General conversations, coding, content generation
• Speed: Fast
• Context: 128K tokens
• Max Output: 8K tokens (default 4K)
• Mode: Non-thinking (can enable thinking via parameter)
• Features: Thinking mode, JSON mode, function calling, FIM completion
• Pricing: $0.028/1M cache hit, $0.28/1M cache miss, $0.42/1M output

deepseek-reasoner

• Best for: Complex reasoning, math, logic problems, multi-step tasks
• Speed: Slower (shows thinking process)
• Context: 128K tokens
• Max Output: 64K tokens (default 32K)
• Mode: Thinking (always active, chain-of-thought reasoning)
• Features: JSON mode, function calling
• Output: Both reasoning process and final answer
• Pricing: $0.028/1M cache hit, $0.28/1M cache miss, $0.42/1M output

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
DEFAULT_MODEL	deepseek-chat	Default model for requests
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
SKIP_CONNECTION_TEST	false	Skip startup API connection test
MAX_MESSAGE_LENGTH	100000	Maximum message content length (characters)
SESSION_TTL_MINUTES	30	Session time-to-live in minutes
MAX_SESSIONS	100	Maximum number of concurrent sessions
FALLBACK_ENABLED	true	Enable automatic model fallback on errors
CIRCUIT_BREAKER_THRESHOLD	5	Consecutive failures before circuit opens
CIRCUIT_BREAKER_RESET_TIMEOUT	30000	Milliseconds before circuit half-opens
MAX_SESSION_MESSAGES	200	Max messages per session (sliding window)
ENABLE_MULTIMODAL	false	Enable multimodal (image) input support
TRANSPORT	stdio	Transport mode: stdio or http
HTTP_PORT	3000	HTTP server port (when TRANSPORT=http)

Example with custom config:

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

Project Structure

deepseek-mcp-server/
├── worker/                  # Cloudflare Worker (remote BYOK endpoint)
│   ├── src/index.ts         # Worker entry point
│   ├── wrangler.toml        # Cloudflare config
│   └── package.json
├── src/
│   ├── index.ts              # Entry point, bootstrap
│   ├── server.ts             # McpServer factory (auto-version)
│   ├── deepseek-client.ts    # DeepSeek API wrapper (circuit breaker + fallback)
│   ├── config.ts             # Centralized config with Zod validation
│   ├── cost.ts               # Cost calculation and formatting
│   ├── schemas.ts            # Zod input validation schemas
│   ├── types.ts              # TypeScript types + type guards
│   ├── errors.ts             # Custom error classes
│   ├── session.ts            # In-memory session store (multi-turn)
│   ├── circuit-breaker.ts    # Circuit breaker pattern
│   ├── usage-tracker.ts      # Usage statistics tracker
│   ├── transport-http.ts     # Streamable HTTP transport (Express)
│   ├── tools/
│   │   ├── deepseek-chat.ts  # deepseek_chat tool (sessions + fallback)
│   │   ├── deepseek-sessions.ts # deepseek_sessions tool
│   │   └── index.ts          # Tool registration aggregator
│   ├── resources/
│   │   ├── models.ts         # deepseek://models resource
│   │   ├── config.ts         # deepseek://config resource
│   │   ├── usage.ts          # deepseek://usage resource
│   │   └── index.ts          # Resource registration aggregator
│   └── prompts/
│       ├── core.ts           # 5 core reasoning prompts
│       ├── advanced.ts       # 5 advanced prompts
│       ├── function-calling.ts # 2 function calling prompts
│       └── index.ts          # Prompt registration aggregator
├── dist/                     # Compiled JavaScript
├── llms.txt                  # AI discoverability index
├── llms-full.txt             # Full docs for LLM context
├── vitest.config.ts          # Test configuration
├── package.json
├── tsconfig.json
└── README.md

Building

npm run build

Watch Mode (for development)

npm run watch

Testing

# Run all tests
npm test

# Watch mode
npm run test:watch

# With coverage report
npm run test:coverage

Testing Locally

# 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.

Remote Endpoint (Hosted)

A hosted BYOK (Bring Your Own Key) endpoint is available at:

https://deepseek-mcp.tahirl.com/mcp

Send your DeepSeek API key as Authorization: Bearer <key>. No server-side API key stored — your key is used directly per request. Powered by Cloudflare Workers (global edge, zero cold start).

Note: The deepseek-reasoner model may take over 30 seconds for complex queries. Some MCP clients (e.g. Claude Code) have built-in tool call timeouts that may interrupt long-running requests. For complex tasks, deepseek-chat is recommended.

# Test health
curl https://deepseek-mcp.tahirl.com/health

# Test MCP (requires auth)
curl -X POST https://deepseek-mcp.tahirl.com/mcp \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{"jsonrpc":"2.0","method":"initialize","params":{"capabilities":{}},"id":1}'

HTTP Transport (Self-Hosted)

Run your own HTTP endpoint:

TRANSPORT=http HTTP_PORT=3000 DEEPSEEK_API_KEY=your-key node dist/index.js

Test the health endpoint:

curl http://localhost:3000/health

The MCP endpoint is available at POST /mcp (Streamable HTTP protocol).

Docker

# Build
docker build -t deepseek-mcp-server .

# Run
docker run -d -p 3000:3000 -e DEEPSEEK_API_KEY=your-key deepseek-mcp-server

# Or use docker-compose
DEEPSEEK_API_KEY=your-key docker compose up -d

The Docker image defaults to HTTP transport on port 3000 with a built-in health check.

Troubleshooting

"DEEPSEEK_API_KEY environment variable is not set"

Option 1: Use the correct installation command

# 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:

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

4. Save and restart Claude Code

"Failed to connect to DeepSeek API"

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

Server not appearing in your MCP client

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

Permission Denied on macOS/Linux

Make the file executable:

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:

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

Contributing

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

Reporting Issues

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

Development

# 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

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Made by @arikusi

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