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Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP

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🧠 MCP server implementing RAT (Retrieval Augmented Thinking) - combines DeepSeek's reasoning with GPT-4/Claude/Mistral responses, maintaining conversation c...

109 stars JavaScriptAI & Machine Learning Updated Oct 3, 2025

Documentation

Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP

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A Model Context Protocol (MCP) server that combines DeepSeek R1's reasoning capabilities with Claude 3.5 Sonnet's response generation through OpenRouter. This implementation uses a two-stage process where DeepSeek provides structured reasoning which is then incorporated into Claude's response generation.

Features

  • Two-Stage Processing:
    • Uses DeepSeek R1 for initial reasoning (50k character context)
    • Uses Claude 3.5 Sonnet for final response (600k character context)
    • Both models accessed through OpenRouter's unified API
    • Injects DeepSeek's reasoning tokens into Claude's context
  • Smart Conversation Management:
    • Detects active conversations using file modification times
    • Handles multiple concurrent conversations
    • Filters out ended conversations automatically
    • Supports context clearing when needed
  • Optimized Parameters:
    • Model-specific context limits:
      • DeepSeek: 50,000 characters for focused reasoning
      • Claude: 600,000 characters for comprehensive responses
    • Recommended settings:
      • temperature: 0.7 for balanced creativity
      • top_p: 1.0 for full probability distribution
      • repetition_penalty: 1.0 to prevent repetition

Installation

Installing via Smithery

To install DeepSeek Thinking with Claude 3.5 Sonnet for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install @newideas99/Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP --client claude

Manual Installation

1. Clone the repository:

bash
git clone https://github.com/yourusername/Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP.git
cd Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP

2. Install dependencies:

bash
npm install

3. Create a `.env` file with your OpenRouter API key:

env
# Required: OpenRouter API key for both DeepSeek and Claude models
OPENROUTER_API_KEY=your_openrouter_api_key_here

# Optional: Model configuration (defaults shown below)
DEEPSEEK_MODEL=deepseek/deepseek-r1  # DeepSeek model for reasoning
CLAUDE_MODEL=anthropic/claude-3.5-sonnet:beta  # Claude model for responses

4. Build the server:

bash
npm run build

Usage with Cline

Add to your Cline MCP settings (usually in `~/.vscode/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json`):

json
{
  "mcpServers": {
    "deepseek-claude": {
      "command": "/path/to/node",
      "args": ["/path/to/Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP/build/index.js"],
      "env": {
        "OPENROUTER_API_KEY": "your_key_here"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Tool Usage

The server provides two tools for generating and monitoring responses:

generate_response

Main tool for generating responses with the following parameters:

typescript
{
  "prompt": string,           // Required: The question or prompt
  "showReasoning"?: boolean, // Optional: Show DeepSeek's reasoning process
  "clearContext"?: boolean,  // Optional: Clear conversation history
  "includeHistory"?: boolean // Optional: Include Cline conversation history
}

check_response_status

Tool for checking the status of a response generation task:

typescript
{
  "taskId": string  // Required: The task ID from generate_response
}

Response Polling

The server uses a polling mechanism to handle long-running requests:

1. Initial Request:

    2. Status Checking:

      Example usage in Cline:

      typescript
      // Initial request
      const result = await use_mcp_tool({
        server_name: "deepseek-claude",
        tool_name: "generate_response",
        arguments: {
          prompt: "What is quantum computing?",
          showReasoning: true
        }
      });
      
      // Get taskId from result
      const taskId = JSON.parse(result.content[0].text).taskId;
      
      // Poll for status (may need multiple checks over ~60 seconds)
      const status = await use_mcp_tool({
        server_name: "deepseek-claude",
        tool_name: "check_response_status",
        arguments: { taskId }
      });
      
      // Example status response when complete:
      {
        "status": "complete",
        "reasoning": "...",  // If showReasoning was true
        "response": "..."    // The final response
      }

      Development

      For development with auto-rebuild:

      bash
      npm run watch

      How It Works

      1. Reasoning Stage (DeepSeek R1):

        2. Response Stage (Claude 3.5 Sonnet):

          License

          MIT License - See LICENSE file for details.

          Credits

          Based on the RAT (Retrieval Augmented Thinking) concept by Skirano, which enhances AI responses through structured reasoning and knowledge retrieval.

          This implementation specifically combines DeepSeek R1's reasoning capabilities with Claude 3.5 Sonnet's response generation through OpenRouter's unified API.

          Frequently asked questions

          What is Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP?

          Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP is 🧠 MCP server implementing RAT (Retrieval Augmented Thinking) - combines DeepSeek's reasoning with GPT-4/Claude/Mistral responses, maintaining conversation c...

          How do I install Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP?

          Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

          Is Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP open source?

          Yes — it is hosted on GitHub at https://github.com/newideas99/Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP and has 109 stars.

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