get-deepseek-thinker

Instructions

Implementation Reference

• src/index.ts:123-151 (handler)

  Executes the get-deepseek-thinker tool: validates input with schema, selects completion method based on environment variable USE_OLLAMA, calls the appropriate helper function, and returns the reasoning content.

  if (name === "get-deepseek-thinker") {
    const { originPrompt } = GetDeepseekThinkerSchema.parse(args);
  
    if (!originPrompt) {
      return {
        content: [
          {
            type: "text",
            text: "Please enter a prompt",
          },
        ],
      };
    }
  
    let result = '';
    if(process?.env?.USE_OLLAMA){
      result = await getOllamaCompletion(originPrompt);
    }else{
      result = await getCompletion(originPrompt);
    }
    return {
      content: [
        {
          type: "text",
          text: result,
        },
      ],
    };
  } else {

• src/index.ts:78-80 (schema)

  Zod schema for validating the tool's input: requires originPrompt as string.

  const GetDeepseekThinkerSchema = z.object({
    originPrompt: z.string(),
  });

• src/index.ts:97-116 (registration)

  Registers the get-deepseek-thinker tool in the ListToolsRequestHandler, providing name, description, and input schema.

  server.setRequestHandler(ListToolsRequestSchema, async () => {
    return {
      tools: [
        {
          name: "get-deepseek-thinker",
          description: "think with deepseek",
          inputSchema: {
            type: "object",
            properties: {
              originPrompt: {
                type: "string",
                description: "user's original prompt",
              },
            },
            required: ["originPrompt"],
          },
        },
      ],
    };
  });

• src/index.ts:15-49 (helper)

  Helper function using OpenAI API to get completion from deepseek-r1 model, collects reasoning_content from stream until content is produced.

  async function getCompletion(_prompt: string) {
    const openai = new OpenAI({
      apiKey: process?.env?.API_KEY,
      baseURL: process?.env?.BASE_URL,
    });
  
    try {
      const completion = await openai.chat.completions.create({
        model: 'deepseek-r1',
        messages: [{ role: 'user', content: _prompt }],
        stream: true  // Change to non-streaming output
      });
  
      let reasoningContent = ''; // For collecting all reasoning_content
      // Handle streaming response
      for await (const chunk of completion) {
        if (chunk.choices) {
          // If there's reasoning_content, add it to the collector
          // @ts-ignore
          if (chunk.choices[0]?.delta?.reasoning_content) {
            // @ts-ignore
            reasoningContent += chunk.choices[0].delta.reasoning_content;
          }
          // When content is received, indicating reasoning is complete, return the collected content
          if (chunk.choices[0]?.delta?.content) {
            return "Answer with given reasoning process: " + reasoningContent;
          }
        }
      }
      // @ts-ignore
      return "Answer with given reasoning process: " + completion.choices[0]?.message?.reasoning_content;
    } catch (error) {
      return `Error: ${error}`
    }
  }

• src/index.ts:52-75 (helper)

  Alternative helper using Ollama to generate from deepseek-r1, collects response until <think> tags are matched, aborts stream then.

  async function getOllamaCompletion(_prompt: string) {
    let reasoningContent = ''; // For collecting all reasoning_content
    try {
      const response = await ollama.generate({
        model: 'deepseek-r1',
        prompt: _prompt,
        stream: true,
      })
      for await (const part of response) {
        reasoningContent = reasoningContent + part.response;
        // Regex matching
        const regex = /<think>([\s\S]*?)<\/think>/i;
        // If contains <think> and </think>, collect thinkContent
        const thinkContent = reasoningContent.match(regex)?.[1]
        if (thinkContent) {
          ollama.abort();
          return "Answer with given reasoning process: " + thinkContent
        }
      }
      return "Answer with given reasoning process: " + reasoningContent
    } catch (error) {
      return `Error: ${error}`
    }
  }