Skip the plumbing.
Start at real product work.

// streaming route with tool selection + telemetry
import { streamText, convertToModelMessages } from 'ai';
import { getModel } from '@/ai/provider';
import { getToolsForRole } from '@/ai/tools';
import { buildSystemPrompt } from '@/ai/system-prompt';

const result = streamText({
  model: getModel('anthropic'),
  system: buildSystemPrompt({ role: 'dev' }),
  messages: await convertToModelMessages(messages),
  tools: getToolsForRole('dev'),
  maxSteps: 50,
  experimental_telemetry: telemetry,
});

return result.toUIMessageStreamResponse();

// merge tools from multiple MCP servers
import { MCPHost } from '@/ai/mcp';

const host = new MCPHost();
await host.connect('http://localhost:3001/sse', 'server-a');
await host.connect('http://localhost:3002/sse', 'server-b');

const mcpTools = host.getTools();

const result = streamText({
  model: getModel('openai'),
  tools: { ...appTools, ...mcpTools },
});

await host.close();

// add your own tool with a typed schema
import { tool } from 'ai';
import { z } from 'zod';

export const weatherTool = tool({
  description: 'Get current weather for a city',
  inputSchema: z.object({
    city: z.string().describe('City name'),
  }),
  execute: async ({ city }) => {
    const res = await fetch(`https://api.weather.example?q=${city}`);
    return res.json();
  },
});

// then register it in src/ai/tools/index.ts