Update agent with new Gemini SDK and MCP integration

conversation-layer-agent/src/index.ts

@@ -1,5 +1,7 @@
 import express from 'express';
-import { GoogleGenerativeAI } from '@google/generative-ai';
+import { GoogleGenAI, mcpToTool } from '@google/genai';
+import { Client } from '@modelcontextprotocol/sdk/client/index.js';
+import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';
 import dotenv from 'dotenv';
 
 dotenv.config();
@@ -8,9 +10,20 @@ const PORT = Number(process.env.PORT) || 8001;
 const API_KEY = process.env.GEMINI_API_KEY || '';
 console.log(`Using Gemini API key: ${API_KEY}`);
 
-const genAI = API_KEY ? new GoogleGenerativeAI(API_KEY) : null;
-const model = genAI ? genAI.getGenerativeModel({ model: 'gemini-pro' }) : null;
+const genAI = API_KEY ? new GoogleGenAI({ apiKey: API_KEY }) : null;
 
+const MCP_URL = process.env.MCP_URL || 'http://planilla.interno.mcp';
+let mcpClient: Client | undefined;
+let mcpTransport: StreamableHTTPClientTransport | undefined;
+
+async function getMcpClient(): Promise<Client> {
+  if (!mcpClient) {
+    mcpClient = new Client({ name: 'planilla-client', version: '1.0.0' });
+    mcpTransport = new StreamableHTTPClientTransport(new URL(MCP_URL));
+    await mcpClient.connect(mcpTransport);
+  }
+  return mcpClient;
+}
 const repoInfo = `This repository contains a WhatsApp router, a simple chat UI and now a conversation-layer-agent service.
 - whatsapp-router: Forwards WhatsApp messages to configured agents. 
 - chat-ui: Minimal web interface that also talks to an agent. 
@@ -24,14 +37,23 @@ app.post('/', async (req, res) => {
   const message = req.body?.message as string | undefined;
   if (!message) return res.status(400).json({ error: 'Missing message' });
 
-  if (!model) {
+  if (!genAI) {
     return res.json({ reply: repoInfo });
   }
 
   try {
-    const prompt = `Repo information: ${repoInfo}\nUser message: ${message}`;
-    const result = await model.generateContent(prompt);
-    const reply = result.response.text().trim();
+    const contents = `Repo information: ${repoInfo}\nUser message: ${message}`;
+    const config: any = {};
+    if (message.toLowerCase().includes('/planilla')) {
+      const client = await getMcpClient();
+      config.tools = [mcpToTool(client)];
+    }
+    const result = await genAI.models.generateContent({
+      model: 'gemini-2.0-flash',
+      contents,
+      config,
+    });
+    const reply = (result.text || '').trim();
     res.json({ reply });
   } catch (err: any) {
     console.error('Gemini error', err.message);