nvkanirudh/linkedin-post-generator

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A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

概要

A Model Context Protocol (MCP) server that automates generating professional LinkedIn post drafts from YouTube videos. This tool streamlines content repurposing by extracting transcripts from YouTube videos, summarizing the content, and generating engaging LinkedIn posts tailored to your preferences. - : Automatically extract transcripts from any YouTube video - : Generate concise summaries with customizable tone and target audience - : Create professional LinkedIn posts with customizable style and tone - : Go from YouTube URL to LinkedIn post in a single operation - : Adjust tone, audience, word count, and more to match your personal brand - : Works seamlessly with AI assistants that support the Model Context Protocol 3. Create a .env file based on the example: This MCP server is designed to work with Claude Desktop and other AI assistants that support the Model Context Protocol. To use it with Claude Desktop: 1.

README

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LinkedIn Post Generator

Features
Installation
- Local Development
- Using with Claude Desktop
Configuration
Usage
- Available Tools
- Workflow Example
Deployment
License

Features

YouTube Transcript Extraction: Automatically extract transcripts from any YouTube video
Content Summarization: Generate concise summaries with customizable tone and target audience
LinkedIn Post Generation: Create professional LinkedIn posts with customizable style and tone
All-in-One Workflow: Go from YouTube URL to LinkedIn post in a single operation
Customization Options: Adjust tone, audience, word count, and more to match your personal brand
MCP Integration: Works seamlessly with AI assistants that support the Model Context Protocol

Installation

Local Development

Clone the repository:

git clone https://github.com/NvkAnirudh/LinkedIn-Post-Generator.git
cd LinkedIn-Post-Generator

Install dependencies:
```
npm install
```
Create a .env file based on the example:
```
cp .env.example .env
```

Add your API keys to the .env file:

OPENAI_API_KEY=your_openai_api_key
YOUTUBE_API_KEY=your_youtube_api_key

Run the server:
```
npm run dev
```
Test with MCP Inspector:
```
npm run inspect
```

Using with Claude Desktop

This MCP server is designed to work with Claude Desktop and other AI assistants that support the Model Context Protocol. To use it with Claude Desktop:

Configure Claude Desktop by editing the configuration file at ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
```
{
  "mcpServers": {
    "linkedin-post-generator": {
      "command": "npx",
      "args": [
```

GitHub で README 全文を見る

インストール

npx -y @smithery/cli@latest run @NvkAnirudh/linkedin-post-generator --key YOUR_SMITHERY_API_KEY --config {\"OPENAI_API_KEY\":\"YOUR_OPENAI_API_KEY\ \"YOUTUBE_API_KEY\":\"YOUR_YOUTUBE_API_KEY\"} --transport stdio

MCP 初心者？mcpskill.org のガイドから始めましょう →

設定

{
     "mcpServers": {
       "linkedin-post-generator": {
         "command": "npx",
         "args": [
           "-y",
           "@smithery/cli@latest",
           "run",
           "@NvkAnirudh/linkedin-post-generator",
           "--key",
           "YOUR_SMITHERY_API_KEY",
           "--config",
           "{\"OPENAI_API_KEY\":\"YOUR_OPENAI_API_KEY\",\"YOUTUBE_API_KEY\":\"YOUR_YOUTUBE_API_KEY\"}",
           "--transport",
           "stdio"
         ]
       }
     }
   }