Upstash

The Upstash storage implementation provides a serverless-friendly storage solution using Upstash's Redis-compatible key-value store.

Pricing

When using Mastra with Upstash, the pay-as-you-go model can result in unexpectedly high costs due to the high volume of Redis commands generated during agent conversations. We strongly recommend using a fixed pricing plan for predictable costs. See Upstash pricing for details and GitHub issue #5850 for context.

Observability Not Supported

Upstash storage doesn't support the observability domain. Traces from the MastraStorageExporter can't be persisted to Upstash, and Studio's observability features won't work with Upstash as your only storage provider. To enable observability, use composite storage to route observability data to a supported provider like ClickHouse.

Installation

npm

npm install @mastra/upstash@latest

pnpm

pnpm add @mastra/upstash@latest

Yarn

yarn add @mastra/upstash@latest

Bun

bun add @mastra/upstash@latest

Usage

import { UpstashStore } from '@mastra/upstash'

const storage = new UpstashStore({
  id: 'upstash-storage',
  url: process.env.UPSTASH_URL,
  token: process.env.UPSTASH_TOKEN,
})

Parameters

url:

string

Upstash Redis URL

token:

string

Upstash Redis authentication token

prefix?:

string

= mastra:

Key prefix for all stored items

Additional notes

Key Structure

The Upstash storage implementation uses a key-value structure:

• Thread keys: {prefix}thread:{threadId}
• Message keys: {prefix}message:{messageId}
• Metadata keys: {prefix}metadata:{entityId}

Serverless Benefits

Upstash storage is particularly well-suited for serverless deployments:

• No connection management needed
• Pay-per-request pricing
• Global replication options
• Edge-compatible

Data Persistence

Upstash provides:

• Automatic data persistence
• Point-in-time recovery
• Cross-region replication options

Performance Considerations

For optimal performance:

• Use appropriate key prefixes to organize data
• Monitor Redis memory usage
• Consider data expiration policies if needed

Usage example

Adding memory to an agent

To add Upstash memory to an agent use the Memory class and create a new storage key using UpstashStore and a new vector key using UpstashVector. The configuration can point to either a remote service or a local setup.

src/mastra/agents/example-upstash-agent.ts

import { Memory } from '@mastra/memory'
import { Agent } from '@mastra/core/agent'
import { UpstashStore } from '@mastra/upstash'

export const upstashAgent = new Agent({
  id: 'upstash-agent',
  name: 'Upstash Agent',
  instructions:
    'You are an AI agent with the ability to automatically recall memories from previous interactions.',
  model: 'openai/gpt-5.6-sol',
  memory: new Memory({
    storage: new UpstashStore({
      id: 'upstash-agent-storage',
      url: process.env.UPSTASH_REDIS_REST_URL!,
      token: process.env.UPSTASH_REDIS_REST_TOKEN!,
    }),
    options: {
      generateTitle: true, // Explicitly enable automatic title generation
    },
  }),
})

Using the agent

Use memoryOptions to scope recall for this request. Set lastMessages: 5 to limit recency-based recall, and use semanticRecall to fetch the topK: 3 most relevant messages, including messageRange: 2 neighboring messages for context around each match.

src/test-upstash-agent.ts

import 'dotenv/config'

import { mastra } from './mastra'

const threadId = '123'
const resourceId = 'user-456'

const agent = mastra.getAgent('upstashAgent')

const message = await agent.stream('My name is Mastra', {
  memory: {
    thread: threadId,
    resource: resourceId,
  },
})

await message.textStream.pipeTo(new WritableStream())

const stream = await agent.stream("What's my name?", {
  memory: {
    thread: threadId,
    resource: resourceId,
  },
  memoryOptions: {
    lastMessages: 5,
    semanticRecall: {
      topK: 3,
      messageRange: 2,
    },
  },
})

for await (const chunk of stream.textStream) {
  process.stdout.write(chunk)
}