Memory threads and resources

Mastra organizes memory into threads, which are records that group related interactions, using two identifiers:

1. thread: A globally unique ID representing the conversation (e.g., support_123). Must be unique across all resources.
2. resource: The user or entity that owns the thread (e.g., user_123, org_456).

The resource is especially important for resource-scoped memory, which allows memory to persist across all threads associated with the same user or entity.

const stream = await agent.stream("message for agent", {
  memory: {
    thread: "user-123",
    resource: "test-123"
  }
});

Mastra Playground sets thread and resource IDs automatically. In your own application, you must provide them manually as part of each .generate() or .stream() call.

Thread title generation

Mastra can automatically generate descriptive thread titles based on the user’s first message. Enable this by setting generateTitle to true. This improves organization and makes it easier to display conversations in your UI.

export const testAgent = new Agent({
  memory: new Memory({
    options: {
      threads: {
        generateTitle: true,
      }
    },
  })
});

Title generation runs asynchronously after the agent responds and does not affect response time. See the full configuration reference for details and examples.

Optimizing title generation

Titles are generated using your agent’s model by default. To optimize cost or behavior, provide a smaller model and custom instructions. This keeps title generation separate from main conversation logic.

export const testAgent = new Agent({
  // ...
  memory: new Memory({
    options: {
      threads: {
        generateTitle: {
          model: openai("gpt-4.1-nano"),
          instructions: "Generate a concise title based on the user's first message",
        },
      },
    }
  })
});

Dynamic model selection and instructions

You can configure thread title generation dynamically by passing functions to model and instructions. These functions receive the runtimeContext object, allowing you to adapt title generation based on user-specific values.

export const testAgent = new Agent({
  // ...
  memory: new Memory({
    options: {
      threads: {
        generateTitle: {
          model: ({ runtimeContext }) => {
            const userTier = runtimeContext.get("userTier");
            return userTier === "premium" ? openai("gpt-4.1") : openai("gpt-4.1-nano");
          },
          instructions: ({ runtimeContext }) => {
            const language = runtimeContext.get("userLanguage") || "English";
            return `Generate a concise, engaging title in ${language} based on the user's first message.`;
          }
        }
      }
    }
  })
});