LinkedIn Post Generator
@NvkAnirudh
About LinkedIn Post Generator
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.
Basic information
Config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTools
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Overview
What is LinkedIn Post Generator?
LinkedIn Post Generator is a Model Context Protocol (MCP) server that automates generating professional LinkedIn post drafts from YouTube videos. It streamlines content repurposing by extracting transcripts, summarizing the content, and generating engaging LinkedIn posts tailored to your preferences.
How to use LinkedIn Post Generator?
Install the server locally by cloning the repository and running npm install, then configure your API keys in a .env file (OpenAI API key required; YouTube API key optional). Run the server with npm run dev and invoke its tools via any MCP-compatible AI assistant (e.g., Claude Desktop). Alternatively, configure Claude Desktop using the provided Smithery integration to pass API keys automatically. Use tools such as extract_transcript, summarize_transcript, generate_linkedin_post, or the all-in-one youtube_to_linkedin_post tool.
Key features of LinkedIn Post Generator
- YouTube transcript extraction from any video URL
- Content summarization with customizable tone and audience
- LinkedIn post generation with adjustable style and tone
- All-in-one workflow from YouTube URL to post
- Customization options for tone, audience, word count
- Seamless integration with MCP‑compatible AI assistants
Use cases of LinkedIn Post Generator
- Repurpose YouTube video content into LinkedIn posts
- Quickly create professional posts from conference talks or webinars
- Automate social media content creation for marketers
- Generate consistent, on‑brand posts for thought leadership
FAQ from LinkedIn Post Generator
What API keys are needed?
An OpenAI API key is required. A YouTube API key is optional but enhances metadata retrieval.
How can I configure this server with Claude Desktop?
Edit your Claude Desktop configuration file (claude_desktop_config.json) to include the Smithery command with your API keys, as shown in the README.
Can I customize the tone of the generated posts?
Yes. The summarization tool supports tones (educational, inspirational, professional, conversational) and the post generation tool supports tones (first‑person, third‑person, thought‑leader).
What tools does this MCP server provide?
It provides set_api_keys, check_api_keys, extract_transcript, summarize_transcript, generate_linkedin_post, and youtube_to_linkedin_post.
Where is the server deployed?
It is deployed on Smithery and can be self‑deployed using the Smithery CLI.
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