Gemini MCP Server

import fetch from 'node-fetch'; import { config } from 'dotenv'; // Load environment variables from .env file config(); const apiKey = process.env.GEMINI_API_KEY; if (!apiKey) { console.error('GEMINI_API_KEY environment variable is required'); process.exit(1); } /** * A simple example showing how to call Gemini directly using the API */ async function callGemini(prompt: string) { const model = 'gemini-2.0-flash'; const url = `https://generativelanguage.googleapis.com/v1beta/models/${model}:generateContent?key=${apiKey}`; const body = { contents: [{ parts: [{ text: prompt }] }] }; try { console.log(`Sending request to Gemini API: "${prompt}"`); const response = await fetch(url, { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify(body), }); if (!response.ok) { const errorText = await response.text(); throw new Error(`API error (${response.status}): ${errorText}`); } const data = await response.json(); if (!data.candidates || !data.candidates[0] || !data.candidates[0].content) { throw new Error('Invalid response from Gemini API'); } // Extract text from response const responseText = data.candidates[0].content.parts .map((part: any) => part.text || '') .join(''); console.log('\nResponse from Gemini:'); console.log('-------------------'); console.log(responseText); console.log('-------------------'); } catch (error) { console.error('Error:', error); } } // Allow running this script directly if (require.main === module) { const prompt = process.argv[2] || 'Explain how AI works in 3 sentences.'; callGemini(prompt); } export { callGemini };