What can you do with this server?

The LinkedIn Post Generator server automates the creation of professional LinkedIn posts from YouTube videos by extracting transcripts, summarizing content, and generating tailored posts. * Extract Transcripts: Pull transcripts directly from YouTube video URLs * Summarize Content: Create concise summaries with customizable tone, audience, and word count * Generate LinkedIn Posts: Craft professional posts with options for tone, hashtags, speaker name, and call-to-action inclusion * All-in-One Workflow: Perform the entire process from YouTube URL to LinkedIn post in a single operation * Set API Keys: Configure OpenAI (required) and YouTube (optional) API keys * Integration: Compatible with AI assistants that support the Model Context Protocol (MCP)

Which integrations are available for this server?

Leverages OpenAI's capabilities to summarize video content and generate professional LinkedIn posts with customizable tone and style. Extracts transcripts from YouTube videos using the YouTube API to enable content summarization and repurposing.

How do I use LinkedIn Post Generator?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@LinkedIn Post Generator generate a LinkedIn post from this YouTube video about AI trends" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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LinkedIn Post Generator

by NvkAnirudh

Overview Schema Related Servers Score Discussions

JavaScript

Hybrid

LinkedIn Post Generator

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.

Related MCP server: YouTube Translate MCP

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": [
        "-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"
      ]
    }
  }
}

Replace:

YOUR_SMITHERY_API_KEY with your Smithery API key
YOUR_OPENAI_API_KEY with your OpenAI API key
YOUR_YOUTUBE_API_KEY with your YouTube API key (optional)

Restart Claude Desktop
In Claude Desktop, you can now access the LinkedIn Post Generator tools without needing to set API keys again

Configuration

The application requires API keys to function properly:

OpenAI API Key (required): Used for content summarization and post generation
YouTube API Key (optional): Enhances YouTube metadata retrieval

You can provide these keys in three ways:

1. Via Claude Desktop Configuration (Recommended)

When using with Claude Desktop and Smithery, the best approach is to include your API keys in the Claude Desktop configuration file as shown in the Using with Claude Desktop section. This way, the keys are automatically passed to the MCP server, and you don't need to set them again.

2. As Environment Variables

When running locally, you can set API keys as environment variables in a .env file:

OPENAI_API_KEY=your_openai_api_key
YOUTUBE_API_KEY=your_youtube_api_key

3. Using the Set API Keys Tool

If you haven't provided API keys through the configuration or environment variables, you can set them directly through the MCP interface using the set_api_keys tool.

Usage

Available Tools

Set API Keys

Tool: set_api_keys
Purpose: Configure your API keys
Parameters:
- openaiApiKey: Your OpenAI API key (required)
- youtubeApiKey: Your YouTube API key (optional)

Check API Keys

Tool: check_api_keys
Purpose: Verify your API key configuration status

Extract Transcript

Tool: extract_transcript
Purpose: Get the transcript from a YouTube video
Parameters:
- youtubeUrl: URL of the YouTube video

Summarize Transcript

Tool: summarize_transcript
Purpose: Create a concise summary of the video content
Parameters:
- transcript: The video transcript text
- tone: Educational, inspirational, professional, or conversational
- audience: General, technical, business, or academic
- wordCount: Approximate word count for the summary (100-300)

Generate LinkedIn Post

Tool: generate_linkedin_post
Purpose: Create a LinkedIn post from a summary
Parameters:
- summary: Summary of the video content
- videoTitle: Title of the YouTube video
- speakerName: Name of the speaker (optional)
- hashtags: Relevant hashtags (optional)
- tone: First-person, third-person, or thought-leader
- includeCallToAction: Whether to include a call to action

All-in-One: YouTube to LinkedIn Post

Tool: youtube_to_linkedin_post
Purpose: Complete workflow from YouTube URL to LinkedIn post
Parameters:
- youtubeUrl: YouTube video URL
- tone: Desired tone for the post
- Plus additional customization options

Workflow Example

Set your API keys using the set_api_keys tool
Use the youtube_to_linkedin_post tool with a YouTube URL
Receive a complete LinkedIn post draft ready to publish

Deployment

This server is deployed on Smithery, a platform for hosting and sharing MCP servers. The deployment configuration is defined in the smithery.yaml file.

To deploy your own instance:

Create an account on Smithery
Install the Smithery CLI:
```
npm install -g @smithery/cli
```
Deploy the server:
```
smithery deploy
```

Contributing

Contributions are welcome and appreciated! Here's how you can contribute to the LinkedIn Post Generator:

Reporting Issues

Use the GitHub issue tracker to report bugs or suggest features
Please provide detailed information about the issue, including steps to reproduce, expected behavior, and actual behavior
Include your environment details (OS, Node.js version, etc.) when reporting bugs

Pull Requests

Fork the repository
Create a new branch (git checkout -b feature/your-feature-name)
Make your changes
Run tests to ensure your changes don't break existing functionality
Commit your changes (git commit -m 'Add some feature')
Push to the branch (git push origin feature/your-feature-name)
Open a Pull Request

Development Guidelines

Follow the existing code style and conventions
Write clear, commented code
Include tests for new features
Update documentation to reflect your changes

Feature Suggestions

If you have ideas for new features or improvements:

Check existing issues to see if your suggestion has already been proposed
If not, open a new issue with the label 'enhancement'
Clearly describe the feature and its potential benefits

Documentation

Improvements to documentation are always welcome:

Fix typos or clarify existing documentation
Add examples or use cases
Improve the structure or organization of the documentation

By contributing to this project, you agree that your contributions will be licensed under the project's MIT License.

License

MIT

Available Tools

6 tools

check_api_keysD

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

extract_transcriptD

ParametersJSON Schema

Name	Required	Description	Default
`youtubeUrl`	Yes	YouTube video URL

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

generate_linkedin_postD

ParametersJSON Schema

Name	Required	Description	Default
`summary`	Yes	Summary of the video content
`videoTitle`	Yes	Title of the YouTube video
`speakerName`	No	Name of the speaker in the video (optional)
`hashtags`	No	Relevant hashtags (optional)
`tone`	No	Tone of the LinkedIn post	first-person
`includeCallToAction`	No	Whether to include a call to action

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

set_api_keysD

ParametersJSON Schema

Name	Required	Description	Default
`openaiApiKey`	Yes	Your OpenAI API key
`youtubeApiKey`	No	Your YouTube API key (optional)

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

summarize_transcriptD

ParametersJSON Schema

Name	Required	Description	Default
`transcript`	Yes	Video transcript text
`tone`	No	Tone of the summary	professional
`audience`	No	Target audience for the summary	general
`wordCount`	No	Approximate word count for the summary

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

youtube_to_linkedin_postD

ParametersJSON Schema

Name	Required	Description	Default
`youtubeUrl`	Yes	YouTube video URL
`tone`	No	Tone of the LinkedIn post	first-person
`summaryTone`	No	Tone of the summary	professional
`audience`	No	Target audience	general
`hashtags`	No	Relevant hashtags (optional)
`includeCallToAction`	No	Whether to include a call to action

TDQS

D1/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

D1.9/5.0

Disambiguation4/5

Most tools have distinct purposes: checking/setting API keys, extracting/summarizing transcripts, generating posts, and a combined YouTube-to-post workflow. However, 'generate_linkedin_post' and 'youtube_to_linkedin_post' could cause some confusion about when to use each, as the latter might implicitly include extraction and summarization steps.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with clear verb-action structures (e.g., 'check_api_keys', 'extract_transcript'). The only minor deviation is 'youtube_to_linkedin_post', which uses a 'source_to_destination' format instead of a verb-noun style, but it remains readable and fits the overall convention.

Tool Count5/5

With 6 tools, this server is well-scoped for its purpose of generating LinkedIn posts from various inputs. Each tool appears to serve a specific function in the workflow, from API management to content processing and post generation, without being overly sparse or bloated.

Completeness3/5

The toolset covers key steps like API setup, content extraction, summarization, and post generation, but there are notable gaps. For example, there's no tool for editing or updating existing posts, managing drafts, or handling post scheduling, which could limit agent workflows in a complete LinkedIn posting lifecycle.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

GitHub Repository

Need Help?

Reddit Discussion

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LinkedIn Post Generator

Table of Contents

Features

Installation

Local Development

Using with Claude Desktop

Configuration

1. Via Claude Desktop Configuration (Recommended)

2. As Environment Variables

3. Using the Set API Keys Tool

Usage

Available Tools

Set API Keys

Check API Keys

Extract Transcript

Summarize Transcript

Generate LinkedIn Post

All-in-One: YouTube to LinkedIn Post

Workflow Example

Deployment

Contributing

Reporting Issues

Pull Requests

Development Guidelines

Feature Suggestions

Documentation

License

Available Tools

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

Appeared in Searches

Latest Blog Posts

MCP directory API