Deepseek Thinker MCP Server

What does “Deepseek Thinker” MCP Server do?

Deepseek Thinker MCP Server acts as a Model Context Protocol (MCP) provider, delivering Deepseek model reasoning content to MCP-enabled AI clients, such as Claude Desktop. It enables AI assistants to access Deepseek’s thought processes and reasoning outputs either through the Deepseek API service or from a local Ollama server. By integrating with this server, developers can enhance their AI workflows with focused reasoning, leveraging either cloud or local inference capabilities. This server is especially useful for scenarios where detailed reasoning chains or chain-of-thought (CoT) outputs are required to inform downstream AI tasks, making it valuable for advanced development, debugging, and AI agent enrichment.

List of Prompts

No explicit prompt templates are mentioned in the repository or documentation.

List of Resources

No explicit MCP resources are detailed in the documentation or codebase.

List of Tools

• get-deepseek-thinker
  • Description: Performs reasoning using the Deepseek model.
  • Input Parameter: originPrompt (string) — The user’s original prompt.
  • Returns: Structured text response containing the reasoning process.

Use Cases of this MCP Server

• AI Reasoning Enhancement
  • Leverage Deepseek’s detailed chain-of-thought outputs to augment AI client responses and provide transparent reasoning steps.
• Integration with Claude Desktop
  • Seamlessly plug into Claude Desktop or similar AI platforms to enable advanced reasoning capabilities via MCP.
• Dual Inference Modes
  • Choose between cloud-based (OpenAI API) or local (Ollama) model inference to suit privacy, cost, or latency needs.
• Developer Debugging & Analysis
  • Use the server to expose and analyze model thinking for research, debugging, and interpretability studies.
• Flexible Deployment
  • Operate the server locally or in cloud environments to suit various workflow requirements.

How to set it up

Windsurf

1. Prerequisites: Ensure Node.js and npx are installed on your system.
2. Configuration File: Locate your Windsurf configuration file (e.g., windsurf_config.json).
3. Add Deepseek Thinker MCP Server: Insert the following JSON snippet into the mcpServers object:

   {
     "deepseek-thinker": {
       "command": "npx",
       "args": [
         "-y",
         "deepseek-thinker-mcp"
       ],
       "env": {
         "API_KEY": "<Your API Key>",
         "BASE_URL": "<Your Base URL>"
       }
     }
   }
   

4. Save and Restart: Save changes and restart Windsurf.
5. Verify: Check the MCP server integration in the Windsurf client.

Claude

1. Prerequisites: Node.js and npx installed.
2. Edit Configuration: Open claude_desktop_config.json.
3. Add MCP Server:

   {
     "mcpServers": {
       "deepseek-thinker": {
         "command": "npx",
         "args": [
           "-y",
           "deepseek-thinker-mcp"
         ],
         "env": {
           "API_KEY": "<Your API Key>",
           "BASE_URL": "<Your Base URL>"
         }
       }
     }
   }
   

4. Save Configuration: Write changes and restart Claude Desktop.
5. Verification: Confirm Deepseek Thinker is available in your MCP tool list.

Cursor

1. Ensure Prerequisites: Node.js and npx must be installed.
2. Locate Cursor Config: Open your Cursor MCP configuration file.
3. Insert MCP Server Details:

   {
     "mcpServers": {
       "deepseek-thinker": {
         "command": "npx",
         "args": [
           "-y",
           "deepseek-thinker-mcp"
         ],
         "env": {
           "API_KEY": "<Your API Key>",
           "BASE_URL": "<Your Base URL>"
         }
       }
     }
   }
   

4. Save & Restart: Apply changes and restart Cursor.
5. Check Integration: Validate that Deepseek Thinker is operational.

Cline

1. Prerequisites: Make sure Node.js and npx are ready.
2. Edit Cline Config: Open the Cline configuration file.
3. Add MCP Server Block:

   {
     "mcpServers": {
       "deepseek-thinker": {
         "command": "npx",
         "args": [
           "-y",
           "deepseek-thinker-mcp"
         ],
         "env": {
           "API_KEY": "<Your API Key>",
           "BASE_URL": "<Your Base URL>"
         }
       }
     }
   }
   

4. Save and Restart: Save the configuration and restart Cline.
5. Verify Functionality: Ensure the server is listed and accessible.

Note: Securing API Keys

For all platforms, API keys and sensitive configuration values should be provided using environment variables in the env section. Example:

{
  "mcpServers": {
    "deepseek-thinker": {
      "command": "npx",
      "args": [
        "-y",
        "deepseek-thinker-mcp"
      ],
      "env": {
        "API_KEY": "<Your API Key>",
        "BASE_URL": "<Your Base URL>"
      }
    }
  }
}

For local Ollama mode, set USE_OLLAMA to "true" in the env object:

"env": {
  "USE_OLLAMA": "true"
}

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-thinker": {
    "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-thinker” to your actual MCP server name and set the correct URL.

Overview

Based on the two tables below, Deepseek Thinker MCP Server provides a focused tool for reasoning integration, is easy to set up, but lacks detailed prompt templates and explicit resource definitions. The project is open source, has a moderate following, and supports secure credential handling. It scores a 6/10 for overall completeness and utility as an MCP server.

MCP Score