YouTube to LinkedIn MCP Server

Name: YouTube to LinkedIn MCP Server
Author: NvkAnirudh

@NvkAnirudh

リポジトリ

YouTube to LinkedIn MCP Server について

概要はまだありません

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

NvkAnirudh

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

What transport does the server use?

The server uses HTTP (FastAPI) with standard REST endpoints. It does not mention any other transport protocols.

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