DeepSeek MCP Server

What does “DeepSeek” MCP Server do?

The DeepSeek MCP Server is a Model Context Protocol (MCP) server designed to integrate DeepSeek’s advanced language models with MCP-compatible applications, such as Claude Desktop. Acting as a bridge, it allows AI assistants to connect with DeepSeek’s APIs, facilitating tasks like language generation, text analysis, and more. The server operates as a proxy, ensuring that API requests are handled securely and anonymously—only the proxy server is visible to the DeepSeek API, not the client. This design enhances privacy, streamlines workflow integration, and empowers developers and AI tools to leverage DeepSeek’s capabilities for improved development, research, and automation.

List of Prompts

No prompt templates were listed in the repository or documentation.

List of Resources

No explicit MCP resources are documented in the repository or README.

List of Tools

No explicit list of tools or tool functions are described in the README or visible repository contents.

Use Cases of this MCP Server

• Anonymized API Access: Developers can interact with DeepSeek’s language models securely, as the server acts as a proxy, protecting client identity and API keys.
• Integration with MCP-Compatible Apps: Enables seamless use of DeepSeek models in tools like Claude Desktop and potentially others supporting MCP.
• Enhanced AI Workflows: Allows developers and researchers to automate content generation, summarization, or analysis using DeepSeek’s models in their existing MCP-based systems.
• Privacy-Preserving Development: Suitable for scenarios where direct API exposure is a concern, maintaining privacy and compliance.
• Scalable Language Model Access: Facilitates scalable and standardized access to DeepSeek’s language models across various AI and automation platforms.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Locate the Windsurf configuration file (e.g., windsurf.config.json).
3. Add the DeepSeek MCP Server to the mcpServers section with a command and arguments.
4. Save the configuration file and restart Windsurf.
5. Verify the server is running and accessible from Windsurf.

{
  "mcpServers": {
    "deepseek-mcp": {
      "command": "npx",
      "args": ["@deepseek/mcp-server@latest"]
    }
  }
}

Claude

1. Ensure Node.js is installed.
2. Open Claude’s configuration file.
3. Insert the DeepSeek MCP Server configuration under the mcpServers object.
4. Save and restart Claude.
5. Confirm the DeepSeek MCP Server is reachable by running a test prompt.

{
  "mcpServers": {
    "deepseek-mcp": {
      "command": "npx",
      "args": ["@deepseek/mcp-server@latest"]
    }
  }
}

Cursor

1. Make sure Node.js is available.
2. Edit the Cursor configuration file.
3. Add the DeepSeek MCP Server configuration to the mcpServers section.
4. Save changes and restart Cursor.
5. Test integration by running a supported task.

{
  "mcpServers": {
    "deepseek-mcp": {
      "command": "npx",
      "args": ["@deepseek/mcp-server@latest"]
    }
  }
}

Cline

1. Install Node.js if not present.
2. Access the Cline configuration file.
3. Add the DeepSeek MCP Server entry to the mcpServers.
4. Save and restart Cline.
5. Ensure functionality with a sample request.

{
  "mcpServers": {
    "deepseek-mcp": {
      "command": "npx",
      "args": ["@deepseek/mcp-server@latest"]
    }
  }
}

Securing API Keys

Store your DeepSeek API key in an environment variable for security. Pass it to the server using the env section:

{
  "mcpServers": {
    "deepseek-mcp": {
      "command": "npx",
      "args": ["@deepseek/mcp-server@latest"],
      "env": {
        "DEEPSEEK_API_KEY": "${DEEPSEEK_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "deepseek-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “deepseek-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Roots support: Not mentioned

I would rate this MCP server a 4/10 for documentation and practical utility based on the README and repository contents. While the setup and privacy features are clear, there is a lack of detail on prompts, resources, and tools, which limits usability for advanced MCP workflows.

MCP Score