Theq

🚀 TypeScript & Node.js Project for MCP Server

This project combines TypeScript with Node.js for MCP servers. It leverages the LLM Studio API to optimize answers and features dynamic prompt optimization, offering efficient and intelligent solutions for MCP - related tasks.

🚀 Quick Start

The project integrates TypeScript and Node.js to build an MCP server. It uses the LLM Studio API to optimize answers and implements dynamic prompt optimization.

💻 Usage Examples

Basic Usage

// Here should be the basic usage code of TypeScript and Node.js related to MCP server
// For example, setting up a simple server
import http from 'http';

const server = http.createServer((req, res) => {
    res.writeHead(200, { 'Content-Type': 'text/plain' });
    res.end('Hello, MCP Server!\n');
});

server.listen(3000, '127.0.0.1', () => {
    console.log('Server running at http://127.0.0.1:3000/');
});

Advanced Usage

// Here should be the advanced usage code related to LLM Studio API and dynamic prompt optimization
// For example, making a request to the LLM Studio API
import axios from 'axios';

async function getOptimizedAnswer(prompt: string) {
    try {
        const response = await axios.post('https://llm-studio-api-url.com', {
            prompt: prompt
        });
        return response.data;
    } catch (error) {
        console.error('Error getting optimized answer:', error);
        return null;
    }
}

const prompt = 'Your dynamic prompt here';
getOptimizedAnswer(prompt).then((answer) => {
    if (answer) {
        console.log('Optimized answer:', answer);
    }
});