Deepseek R1 MCP Server
[](https://mseep.ai/app/66julienmartin-mcp-server-deepseek-r1)
# Deepseek R1 MCP Server
A Model Context Protocol (MCP) server implementation for the Deepseek R1 language model. Deepseek R1 is a powerful language model optimized for reasoning tasks with a context window of 8192 tokens.
Why Node.js?
This implementation uses Node.js/TypeScript as it provides the most stable integration with MCP servers. The Node.js SDK offers better type safety, error handling, and compatibility with Claude Desktop.
<a href="https://glama.ai/mcp/servers/qui5thpyvu"><img width="380" height="200" src="https://glama.ai/mcp/servers/qui5thpyvu/badge" alt="Deepseek R1 Server MCP server" /></a>
## Quick Start
### Installing manually
```bash
# 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
```
## Prerequisites
- Node.js (v18 or higher)
- npm
- Claude Desktop
- Deepseek API key
## Model Selection
By default, this server uses the **deepseek-R1** model. If you want to use **DeepSeek-V3** instead, modify the model name in `src/index.ts`:
```typescript
// For DeepSeek-R1 (default)
model: "deepseek-reasoner"
// For DeepSeek-V3
model: "deepseek-chat"
```
## Project Structure
```
deepseek-r1-mcp/
├── src/
│ ├── index.ts # Main server implementation
├── build/ # Compiled files
│ ├── index.js
├── LICENSE
├── README.md
├── package.json
├── package-lock.json
└── tsconfig.json
```
## Configuration
1. Create a `.env` file:
```
DEEPSEEK_API_KEY=your-api-key-here
```
2. Update Claude Desktop configuration:
```json
{
"mcpServers": {
"deepseek_r1": {
"command": "node",
"args": ["/path/to/deepseek-r1-mcp/build/index.js"],
"env": {
"DEEPSEEK_API_KEY": "your-api-key"
}
}
}
}
```
## Development
```bash
npm run dev # Watch mode
npm run build # Build for production
```
## Features
- Advanced text generation with Deepseek R1 (8192 token context window)
- Configurable parameters (max_tokens, temperature)
- Robust error handling with detailed error messages
- Full MCP protocol support
- Claude Desktop integration
- Support for both DeepSeek-R1 and DeepSeek-V3 models
## API Usage
```typescript
{
"name": "deepseek_r1",
"arguments": {
"prompt": "Your prompt here",
"max_tokens": 8192, // Maximum tokens to generate
"temperature": 0.2 // Controls randomness
}
}
```
## The Temperature Parameter
The default value of `temperature` is 0.2.
Deepseek recommends setting the `temperature` according to your specific use case:
| USE CASE | TEMPERATURE | EXAMPLE |
|----------|-------------|---------|
| Coding / Math | 0.0 | Code generation, mathematical calculations |
| Data Cleaning / Data Analysis | 1.0 | Data processing tasks |
| General Conversation | 1.3 | Chat and dialogue |
| Translation | 1.3 | Language translation |
| Creative Writing / Poetry | 1.5 | Story writing, poetry generation |
## Error Handling
The server provides detailed error messages for common issues:
- API authentication errors
- Invalid parameters
- Rate limiting
- Network issues
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
MIT
TDQS
Scored across 1 tool
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.
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.
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.
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.