What is the two-stage processing?
DeepSeek R1 first generates reasoning tokens, then Claude 3.5 Sonnet uses those as context to produce the final response.
@newideas99
基本信息
🧠 MCP server implementing RAT (Retrieval Augmented Thinking) - combines DeepSeek's reasoning with GPT-4/Claude/Mistral responses, maintaining conversation context between interactions.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@newideas99/Deepseek-Thinking-Claude-3.5-Sonnet-CLINE-MCP",
"--client",
"claude"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
A Model Context Protocol (MCP) server that combines DeepSeek R1's reasoning capabilities with Claude 3.5 Sonnet's response generation through OpenRouter's unified API. It uses a two-stage process where DeepSeek provides structured reasoning which is then incorporated into Claude's response generation. Designed for users of Cline (Claude Dev) who want enhanced reasoning for complex tasks.
Install via Smithery or manually, clone the repository, install dependencies, and set your OpenRouter API key in a .env file. Build the server and add it to your Cline MCP settings. Two tools are available: generate_response (sends a prompt with optional reasoning display) and check_response_status (polls for task completion, which may take up to 60 seconds).
DeepSeek R1 first generates reasoning tokens, then Claude 3.5 Sonnet uses those as context to produce the final response.
Yes, both models are accessed through OpenRouter's unified API. Set `OPENROUTER_API_KEY` in your `.env` file.
DeepSeek uses 50,000 characters for focused reasoning; Claude uses 600,000 characters for comprehensive responses.
Use the `check_response_status` tool with the `taskId` returned by `generate_response`. Poll until the status is "complete".
Yes, set `showReasoning` to `true` in `generate_response` to include DeepSeek's reasoning in the output.

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