YouTube to LinkedIn MCP Server

Name: YouTube to LinkedIn MCP Server
Author: NvkAnirudh

@NvkAnirudh

Repository

About YouTube to LinkedIn MCP Server

No overview available yet

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "YT-to-LinkedIn-MCP-Server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is YouTube to LinkedIn MCP Server?

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. It extracts transcripts, summarizes them using OpenAI GPT, and produces professional, editable LinkedIn post content.

How to use YouTube to LinkedIn MCP Server?

Clone the repository, set up a Python 3.8+ virtual environment, install dependencies, and configure environment variables (OPENAI_API_KEY, YOUTUBE_API_KEY). Run with uvicorn app.main:app --reload for local development, or deploy via Docker or Smithery. Access the API at http://localhost:8000/docs.

Key features of YouTube to LinkedIn MCP Server

YouTube transcript extraction from video URLs
Transcript summarization via OpenAI GPT
Professional LinkedIn post generation with customizable tone
Modular FastAPI endpoints for each pipeline step
Docker and Smithery deployment support

Use cases of YouTube to LinkedIn MCP Server

Content creators repurposing YouTube videos into LinkedIn posts
Social media managers automating post drafts from video content
Professionals quickly generating thought-leadership posts from educational videos
Teams integrating YouTube-to-LinkedIn workflows into existing MCP tools

FAQ from YouTube to LinkedIn MCP Server

What API keys are required?

OpenAI API key is required for summarization and post generation. YouTube Data API key is optional but recommended for better video metadata. Keys can be set as environment variables or provided in each request.

Can I run this server locally without Docker?

Yes. Clone the repository, create a Python virtual environment, install dependencies, set environment variables, and run with uvicorn app.main:app --reload.

What is the default port and how do I change it?

The server runs on port 8000 by default. You can change it by setting the PORT environment variable.

Are the API keys mandatory in environment variables?

No. API keys can be provided per request via the optional fields in endpoint bodies. However, setting them as environment variables is recommended for local development.