Mastra

Receive messages through Flow, run your Mastra agent and deliver its answer as chat bubbles. Keep the agent’s existing tools and workflows.

TypeScript

// npm install @flow-engineer/messaging @mastra/core @ai-sdk/openai
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
import { FlowMessaging, contentText } from "@flow-engineer/messaging";

const flow = new FlowMessaging();
const agent = new Agent({
  id: "bakery-assistant",
  name: "Bakery assistant",
  instructions: "You help customers of Asha's Bakery with orders and delivery. Keep answers short.",
  model: openai("gpt-4.1-mini"),
});

for await (const event of flow.events.stream({ types: ["message.received"] })) {
  const stream = await agent.stream(contentText(event.data.message.content));
  await event.conversation.reply(stream); // reads stream.textStream
}

How it fits

• reply() reads the stream’s textStream, keeps typing on and sends a bubble at each paragraph break.
• Mastra memory: use the Flow conversation.id as the thread ID and conversation.contact (the contact’s ID) as the resource ID, so each person keeps their own history.
• In a Mastra server, receive Flow webhooks on a custom route and call the same code; verify signatures with flow.webhooks.constructEvent(rawBody, signatureHeader, secret), which returns the typed event with event.conversation ready to reply on. See Events and webhooks.
• To see each turn’s model and tool calls and get every reply graded, send this agent’s traces to Flow Observe: Traces from agent frameworks.

Full example

examples/mastra on GitHub.