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Agent memory

Agents use memory to maintain context across interactions. LLMs are stateless and don't retain information between calls, so agents need memory to track message history and recall relevant information.

Mastra agents can be configured to store message history, with optional working memory to maintain recent context, semantic recall to retrieve past messages based on meaning, or observational memory for automatic long-term memory that compresses conversations as they grow.

When to use memory
Direct link to When to use memory

Use memory when your agent needs to maintain multi-turn conversations that reference prior exchanges, recall user preferences or facts from earlier in a session, or build context over time within a conversation thread. Skip memory for single-turn requests where each interaction is independent.

Setting up memory
Direct link to Setting up memory

To enable memory in Mastra, install the @mastra/memory package along with a storage provider.

npm install @mastra/memory@latest @mastra/libsql@latest

Storage providers
Direct link to Storage providers

Memory requires a storage provider to persist message history, including user messages and agent responses. For more details on available providers and how storage works in Mastra, see the Storage documentation.

Configuring memory
Direct link to Configuring memory

  1. Enable memory by creating a Memory instance and passing it to the agent’s memory option.

    src/mastra/agents/memory-agent.ts
    import { Agent } from '@mastra/core/agent'
    import { Memory } from '@mastra/memory'

    export const memoryAgent = new Agent({
      id: 'memory-agent',
      name: 'Memory Agent',
      memory: new Memory({
        options: {
          lastMessages: 20,
        },
      }),
    })
    info

    Visit Memory Class for a full list of configuration options.

  2. Add a storage provider to your main Mastra instance to enable memory across all configured agents.

    src/mastra/index.ts
    import { Mastra } from '@mastra/core'
    import { LibSQLStore } from '@mastra/libsql'

    export const mastra = new Mastra({
      storage: new LibSQLStore({
        id: 'mastra-storage',
        url: ':memory:',
      }),
    })
    info

    Visit libSQL Storage for a full list of configuration options.

Alternatively, add storage directly to an agent’s memory to keep data separate or use different providers per agent.

src/mastra/agents/memory-agent.ts
import { Agent } from '@mastra/core/agent'
import { Memory } from '@mastra/memory'
import { LibSQLStore } from '@mastra/libsql'

export const memoryAgent = new Agent({
  id: 'memory-agent',
  name: 'Memory Agent',
  memory: new Memory({
    storage: new LibSQLStore({
      id: 'mastra-storage',
      url: ':memory:',
    }),
  }),
})
Mastra Cloud Store limitation

Agent-level storage is not supported when using Mastra Cloud Store. If you use Mastra Cloud Store, configure storage on the Mastra instance instead. This limitation does not apply if you bring your own database.

Message history
Direct link to Message history

Include a memory object with both resource and thread to track message history during agent calls.

  • resource: A stable identifier for the user or entity.
  • thread: An ID that isolates a specific conversation or session.

These fields tell the agent where to store and retrieve context, enabling persistent, thread-aware memory across a conversation.

const response = await memoryAgent.generate('Remember my favorite color is blue.', {
  memory: {
    resource: 'user-123',
    thread: 'conversation-123',
  },
})

To recall information stored in memory, call the agent with the same resource and thread values used in the original conversation.

const response = await memoryAgent.generate("What's my favorite color?", {
  memory: {
    resource: 'user-123',
    thread: 'conversation-123',
  },
})
warning

Each thread has an owner (resourceId) that cannot be changed after creation. Avoid reusing the same thread ID for threads with different owners, as this will cause errors when querying.

To learn more about memory see the Memory documentation.

Observational Memory
Direct link to Observational Memory

For long-running conversations, raw message history grows until it fills the context window, degrading agent performance. Observational Memory solves this by running background agents that compress old messages into dense observations, keeping the context window small while preserving long-term memory.

src/mastra/agents/memory-agent.ts
import { Agent } from '@mastra/core/agent'
import { Memory } from '@mastra/memory'

export const memoryAgent = new Agent({
  id: 'memory-agent',
  name: 'Memory Agent',
  memory: new Memory({
    options: {
      observationalMemory: true,
    },
  }),
})

Setting observationalMemory: true uses google/gemini-2.5-flash as the default model for the Observer and Reflector. To use a different model or customize thresholds, pass a config object:

src/mastra/agents/memory-agent.ts
import { Agent } from '@mastra/core/agent'
import { Memory } from '@mastra/memory'

export const memoryAgent = new Agent({
  id: 'memory-agent',
  name: 'Memory Agent',
  memory: new Memory({
    options: {
      observationalMemory: {
        model: 'deepseek/deepseek-reasoner',
        observation: {
          messageTokens: 20_000,
        },
      },
    },
  }),
})
info

See Observational Memory for details on how observations and reflections work, and the reference for all configuration options.

Using RequestContext
Direct link to using-requestcontext

Use RequestContext to access request-specific values. This lets you conditionally select different memory or storage configurations based on the context of the request.

src/mastra/agents/memory-agent.ts
export type UserTier = {
  'user-tier': 'enterprise' | 'pro'
}

const premiumMemory = new Memory()

const standardMemory = new Memory()

export const memoryAgent = new Agent({
  id: 'memory-agent',
  name: 'Memory Agent',
  memory: ({ requestContext }) => {
    const userTier = requestContext.get('user-tier') as UserTier['user-tier']

    return userTier === 'enterprise' ? premiumMemory : standardMemory
  },
})
info

Visit Request Context for more information.

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