X Post MCP

🚀 X-Post MCP

A powerful integrated tool that allows AI models to directly publish content to X (formerly Twitter) via the Model Context Protocol (MCP)

🚀 Quick Start

X-Post MCP is a client-server application that enables AI models to create and publish posts on the X (formerly Twitter) platform. It utilizes the Model Context Protocol to achieve seamless integration between AI models and the X platform.

1. Install Dependencies

Server Installation

cd server
npm install express @types/express

Client Installation

cd client
npm install @tensorflow/tfjs @tensorflow-models/generative-ai

2. Configure Environment Variables

Create a .env file in the server root directory and add the following content:

TWITTER_API_KEY=your_api_key
TWITTER_API_SECRET_KEY=your_api_secret_key
TWITTER_BEARER_TOKEN=your_bearer_token
GEMINI_API_KEY=your_gemini_api_key

3. Start the Services

Start the Server

cd server
npm run dev

The service will run at http://localhost:3001.

Start the Client

cd client
npm run index.ts

✨ Features

• 🔄 Seamless integration with the X (Twitter) API
• 🧠 AI-powered post generation using Google's Gemini model
• 🛠️ MCP server endpoints for X posting functionality
• 💬 Interactive chat interface for testing and demonstration
• 🔒 Secure handling of API credentials
• ✂️ Automatic truncation of posts exceeding X's character limit

📦 Installation

1. Install Dependencies

Server Installation

cd server
npm install express @types/express

Client Installation

cd client
npm install @tensorflow/tfjs @tensorflow-models/generative-ai

2. Configure Environment Variables

Create a .env file in the server root directory and add the following content:

TWITTER_API_KEY=your_api_key
TWITTER_API_SECRET_KEY=your_api_secret_key
TWITTER_BEARER_TOKEN=your_bearer_token
GEMINI_API_KEY=your_gemini_api_key

3. Start the Services

Start the Server

cd server
npm run dev

The service will run at http://localhost:3001.

Start the Client

cd client
npm run index.ts

💻 Usage Examples

Basic Usage

You: Post a tweet about the beautiful weather today

The AI model will generate content using Gemini and send it to the X platform via the MCP tool.

Advanced Usage

Customize Posting Rules

In the server/src/tools/createPost.ts file, you can customize the posting logic as needed:

export async function createPost(context: Context, args: string[]) {
  const message = await gemini.generate(args.join(' '));
  return { status: 'success', message };
}

Extend AI Capabilities

By replacing or extending the client/src/models/gemini.ts file, you can support more AI models.

📚 Documentation

Project Architecture

• Server-side: Based on the Express framework, it provides MCP protocol support and implements long-polling communication through Server-Sent Events (SSE).
• Client-side: An interface tool for connecting to the MCP server and interacting with AI models.

Core Functions

1. AI Content Generation: Generate high-quality text using Google Gemini model.
2. X Platform Posting: Publish content to the target account via the Twitter API.
3. Real-time Communication: Implement two-way data flow between the client and the server using SSE.

🔧 Technical Details

• Bun: A fast all-in-one JavaScript runtime.
• TypeScript: Type-safe JavaScript.
• Express: An efficient web application framework.
• Server-Sent Events (SSE): A real-time communication protocol.

📄 License

This project is licensed under the MIT License. Please refer to the LICENSE file for details.

🤝 Contribution Guidelines

Contributions are welcome! Please follow these steps to submit your PR:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/amazing-feature).
3. Commit your changes (git commit -m 'Add some amazing feature').
4. Push to the remote branch (git push origin feature/amazing-feature).
5. Submit a Pull Request.

🙏 Acknowledgments

Thanks to the following projects for their contributions:

• Model Context Protocol for providing a standardized AI context protocol.
• Twitter API v2 for supporting X platform integration.
• Google Gemini for providing powerful AI capabilities.