Database · MODEL CONTEXT PROTOCOL
NvkAnirudh YT to LinkedIn MCP Server
NvkAnirudh YT to LinkedIn MCP Server is a community-listed Model Context Protocol server. Review the source repository before installation.
WHAT IT CONNECTS
What NvkAnirudh YT to LinkedIn MCP Server gives an AI Agent
- **YouTube Transcript Extraction**: Extract transcripts from YouTube videos using video URLs
- **Transcript Summarization**: Generate concise summaries of video content using OpenAI GPT
- **LinkedIn Post Generation**: Create professional LinkedIn post drafts with customizable tone and style
- **Modular API Design**: Clean FastAPI implementation with well-defined endpoints
- **Containerized Deployment**: Ready for deployment on Smithery
- Python 3.8+
- Docker (for containerized deployment)
- OpenAI API Key
- YouTube Data API Key (optional, but recommended for better metadata)
- Clone the repository:
- Create a virtual environment and install dependencies:
- Create a `.env` file in the project root with your API keys:
- Run the application:
- Access the API documentation at http://localhost:8000/docs
- Build the Docker image:
- Run the container:
- Ensure you have the Smithery CLI installed and configured.
- Deploy to Smithery:
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.