YouTube to LinkedIn MCP Server
by MCP-Mirror
This is a Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. It provides high-quality, editable content drafts based on YouTube video transcripts.
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What is YouTube to LinkedIn MCP Server?
The YouTube to LinkedIn MCP Server is a FastAPI application designed to extract transcripts from YouTube videos, summarize them using OpenAI's GPT models, and generate professional LinkedIn post drafts. It offers a modular API for easy integration and can be deployed using Docker or Smithery.
How to use YouTube to LinkedIn MCP Server?
To use the server, you can either deploy it locally using Python and pip, or deploy it using Docker or Smithery. After deployment, you can access the API endpoints to extract transcripts, summarize them, and generate LinkedIn posts. You will need to provide a YouTube video URL and optionally OpenAI and YouTube API keys.
Key features of YouTube to LinkedIn MCP Server
YouTube Transcript Extraction
Transcript Summarization using OpenAI GPT
LinkedIn Post Generation with customizable tone and style
Modular API Design (FastAPI)
Containerized Deployment (Docker)
Use cases of YouTube to LinkedIn MCP Server
Automating LinkedIn content creation from YouTube videos
Generating summaries of video content for social media
Creating professional LinkedIn posts for video creators
Saving time and effort in crafting social media content
Improving engagement on LinkedIn with relevant video-based content
FAQ from YouTube to LinkedIn MCP Server
What is an MCP server?
What is an MCP server?
MCP stands for Model Context Protocol, a framework for building modular and interoperable AI-powered services.
Do I need an OpenAI API key?
Do I need an OpenAI API key?
Yes, an OpenAI API key is required for transcript summarization and LinkedIn post generation. You can optionally provide it in each request or set it as an environment variable.
Do I need a YouTube Data API key?
Do I need a YouTube Data API key?
A YouTube Data API key is optional but recommended for fetching video metadata. You can provide your own key in the request body.
How do I deploy this server?
How do I deploy this server?
You can deploy the server locally using Python, or using Docker or Smithery for containerized deployment. Refer to the Setup Instructions in the README for detailed steps.
What are the available API endpoints?
What are the available API endpoints?
The server provides endpoints for transcript extraction, transcript summarization, LinkedIn post generation, and output formatting. Refer to the API Endpoints section in the README for details on each endpoint.