generate_linkedin_post

Implementation Reference

• src/modules/post-generator.js:14-99 (handler)

  Core handler function that generates a LinkedIn post using OpenAI GPT based on video summary, title, speaker, hashtags, tone, etc.

  export async function generateLinkedInPost(
    summary, 
    videoTitle, 
    speakerName = null, 
    hashtags = [], 
    tone = "first-person", 
    includeCallToAction = true,
    apiKey
  ) {
    if (!apiKey) {
      throw new Error("OpenAI API key not provided");
    }
    
    if (!summary || summary.trim().length === 0) {
      throw new Error("Empty summary provided");
    }
    
    console.log(`Generating LinkedIn post with tone: ${tone}`);
    
    try {
      // Initialize OpenAI client with provided API key
      const openai = new OpenAI({
        apiKey: apiKey,
      });
      
      // Prepare hashtag string
      const hashtagString = hashtags && hashtags.length > 0 
        ? hashtags.map(tag => tag.startsWith('#') ? tag : `#${tag}`).join(' ')
        : '';
      
      // Prepare speaker reference
      const speakerReference = speakerName ? `by ${speakerName}` : '';
      
      const response = await openai.chat.completions.create({
        model: "gpt-3.5-turbo",
        messages: [
          {
            role: "system",
            content: `You are a professional LinkedIn content creator. 
            Create a compelling LinkedIn post in a ${tone} tone based on the provided video summary.
            The post should be between 500-1200 characters (not including hashtags).
            
            Structure the post with:
            1. An attention-grabbing hook
            2. 2-3 key insights from the video
            3. A personal reflection or takeaway
            ${includeCallToAction ? '4. A soft call to action (e.g., asking a question, inviting comments)' : ''}
            
            The post should feel authentic, professional, and valuable to LinkedIn readers.
            Avoid clickbait or overly promotional language.`
          },
          {
            role: "user",
            content: `Create a LinkedIn post based on this YouTube video:
            
            Title: ${videoTitle} ${speakerReference}
            
            Summary:
            ${summary}
            
            ${hashtagString ? `Suggested hashtags: ${hashtagString}` : ''}
            
            Please format the post ready to copy and paste to LinkedIn.`
          }
        ],
        temperature: 0.7,
        max_tokens: 700
      });
      
      if (response.choices && response.choices.length > 0) {
        let post = response.choices[0].message.content.trim();
        
        // Ensure hashtags are at the end if they weren't included
        if (hashtagString && !post.includes(hashtagString)) {
          post += `\n\n${hashtagString}`;
        }
        
        return post;
      } else {
        throw new Error("No post generated");
      }
    } catch (error) {
      console.error("Post generation error:", error);
      throw new Error(`Failed to generate LinkedIn post: ${error.message}`);
    }
  }

• src/server.js:167-220 (registration)

  MCP tool registration for 'generate_linkedin_post' including Zod input schema, wrapper handler that checks API key and calls the core generateLinkedInPost function, and description.

  server.tool(
    "generate_linkedin_post",
    { 
      summary: z.string().describe("Summary of the video content"),
      videoTitle: z.string().describe("Title of the YouTube video"),
      speakerName: z.string().optional().describe("Name of the speaker in the video (optional)"),
      hashtags: z.array(z.string()).optional().describe("Relevant hashtags (optional)"),
      tone: z.enum(["first-person", "third-person", "thought-leader"])
        .default("first-person")
        .describe("Tone of the LinkedIn post"),
      includeCallToAction: z.boolean().default(true)
        .describe("Whether to include a call to action")
    },
    async ({ summary, videoTitle, speakerName, hashtags, tone, includeCallToAction }) => {
      try {
        // Check if OpenAI API key is set
        if (!apiKeyManager.hasOpenAIKey()) {
          throw new Error("OpenAI API key not set. Please use the set_api_keys tool first.");
        }
        
        const post = await generateLinkedInPost(
          summary, 
          videoTitle, 
          speakerName, 
          hashtags, 
          tone, 
          includeCallToAction,
          apiKeyManager.getOpenAIKey()
        );
        
        return {
          content: [{ 
            type: "text", 
            text: JSON.stringify({
              success: true,
              post
            }, null, 2)
          }]
        };
      } catch (error) {
        return {
          content: [{ 
            type: "text", 
            text: JSON.stringify({
              success: false,
              error: error.message
            }, null, 2)
          }],
          isError: true
        };
      }
    },
    { description: "Generate a LinkedIn post draft from a video summary" }
  );

• src/server.js:169-179 (schema)

  Zod schema defining input parameters for the generate_linkedin_post tool.

  { 
    summary: z.string().describe("Summary of the video content"),
    videoTitle: z.string().describe("Title of the YouTube video"),
    speakerName: z.string().optional().describe("Name of the speaker in the video (optional)"),
    hashtags: z.array(z.string()).optional().describe("Relevant hashtags (optional)"),
    tone: z.enum(["first-person", "third-person", "thought-leader"])
      .default("first-person")
      .describe("Tone of the LinkedIn post"),
    includeCallToAction: z.boolean().default(true)
      .describe("Whether to include a call to action")
  },