Provides database support for storing post schedules and content, serving as a backend for the LinkedIn post automation system.
Provides the runtime environment for the MCP server, supporting the LinkedIn post automation functionality through its ecosystem.
Offers database functionality for storing post schedules and content as an alternative to PostgreSQL, enabling local data persistence for the LinkedIn automation service.
LinkedIn Automated Post Creator
This project automates the creation of LinkedIn posts using MCP server integration. It allows users to schedule and create posts automatically on their LinkedIn account.
Architecture
The project follows a modular architecture with the following components:
- MCP Server: Handles message control and scheduling
- LinkedIn API Integration: Manages LinkedIn authentication and post creation
- Scheduler: Manages post scheduling and timing
- Content Generator: Generates or manages post content
- Database: Stores post schedules and content
Project Structure
Setup Instructions
- Install dependencies:
- Configure LinkedIn API credentials in config/config.py
- Run the MCP server:
Features
- Automated LinkedIn post creation
- Customizable post scheduling
- Content management
- MCP server integration
- Real-time post monitoring
Requirements
- Python 3.8+
- LinkedIn API credentials
- MCP server access
- Database (SQLite/PostgreSQL)
Deployment
The project can be deployed on any server with Python support. Follow the deployment guide in docs/deployment.md for detailed instructions.
This server cannot be installed
Automates the creation and scheduling of LinkedIn posts using MCP server integration, allowing users to manage content and automatically publish to their LinkedIn accounts.
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