Connect to MCP servers with AI SDK

import { createGoogleGenerativeAI } from '@ai-sdk/google';
import { streamText, stepCountIs, experimental_createMCPClient, tool } from 'ai';
import { streamResponse } from '@layercode/node-server-sdk';
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';
import z from 'zod';

export const POST = async (request: Request) => {
  const requestBody = await request.json();
  const { conversation_id, text, turn_id } = requestBody;

  return streamResponse(requestBody, async ({ stream }) => {
    // ✅ Create a fresh MCP transport per request
    const transport = new StreamableHTTPClientTransport(new URL('https://docs.layercode.com/mcp'));
    const docsMCP = await experimental_createMCPClient({ transport });

    try {
      const docsTools = await docsMCP.tools();

      const weather = tool({
        description: 'Get the weather in a location',
        inputSchema: z.object({
          location: z.string().describe('The location to get the weather for')
        }),
        execute: async ({ location }) => ({
          location,
          temperature: 72 + Math.floor(Math.random() * 21) - 10
        })
      });

      const { textStream } = streamText({
        model: createGoogleGenerativeAI({ apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY })('gemini-2.5-flash-lite'),
        system: 'You are a helpful assistant.',
        messages: [{ role: 'user', content: text }],
        tools: { weather, ...docsTools },
        toolChoice: 'auto',
        stopWhen: stepCountIs(10),
        onFinish: async ({ response }) => {
          console.log('MCP Response Complete', response);
          stream.end();
        }
      });

      await stream.ttsTextStream(textStream);
    } finally {
      // ✅ Clean up the MCP connection
      await docsMCP.close();
    }
  });
};