mcp-server-example

The AI Agent with MCP Server & Gemini API is designed to facilitate automated interactions and dynamic responses through a combination of advanced technologies. It integrates the Model Context Protocol (MCP) for structured AI interactions, Express.js for a robust backend, and the Gemini API for enhanced LLM reasoning. This setup allows the agent to automate tasks such as posting on Twitter (X) and performing real-time calculations. The use of Server-Sent Events (SSE) ensures live communication, making the agent capable of real-time responses. The tech stack includes Node.js and Express.js for backend operations, while the Gemini API provides the AI framework for reasoning and dynamic interactions. The agent is extendable, allowing for the addition of more tools and prompts to enhance its conversational capabilities.

Features

• MCP Server Integration – Structured tool-based AI interactions
• Express.js Backend – Robust API endpoints for SSE & HTTP messaging
• Gemini AI Integration – Advanced LLM reasoning for dynamic responses
• Twitter (X) Post Automation – Post directly via API (using createPost tool)
• Real-time Communication – Uses Server-Sent Events (SSE) for live AI responses

MCP Tools

• {'createPost': 'Tool for automating Twitter (X) posts directly via API.'}
• {'addTwoNumbers': 'Tool for performing dynamic calculations.'}

Usage with Different Platforms

Node.js

javascript
const express = require('express');
const app = express();

app.post('/postOnX', (req, res) => {
  // Use MCP server to process request
  // Use Gemini API for enhanced response
  // Use Twitter API to publish post
  res.send('Post published on Twitter (X)');
});

app.listen(3000, () => {
  console.log('Server running on port 3000');
});