SDKs

TypeScript SDKs

Use @memexai/sdk for the service or @memexai/core as an in-process runtime.

MemexAI has two TypeScript packages:

  • @memexai/sdk is the recommended TypeScript service client for the containerized MemexAI service.
  • @memexai/core is the advanced direct Postgres runtime.

Service SDK

npm install @memexai/sdk
import { MemexAI } from '@memexai/sdk'

const memex = new MemexAI({
  url: 'http://localhost:8080',
  apiKey: 'dev-agent-key',
})

const memory = memex.forUser({
  userId: 'demo_user',
  actor: 'assistant',
})

const result = await memory.search('What does this user prefer?')
console.log(result.answer ?? result.results)

Advanced: direct Postgres core runtime

npm install @memexai/core
import { createMemex } from '@memexai/core'

const memex = createMemex({
  databaseUrl: process.env.DATABASE_URL!,
})

await memex.migrate()

const memory = memex.forUser({ userId: 'demo_user', actor: 'assistant' })
await memory.write(
  'user/profile.md',
  '# Profile\n\n- Prefers quiet neighborhoods.',
  'captured user preference',
)

await memex.end()

Toolsets

const system = await memory.getSystemPrompt('You are a helpful assistant with durable user memory.')
const agenticTools = memory.createAgenticToolset()
const rawTools = memory.createRawToolset()

Use system in your model call alongside the toolset. For lower-level control, memory.getPromptBlock() returns only the MemexAI memory section so you can compose the final system prompt yourself.

Framework adapters

Named adapter imports are available for specific frameworks:

FrameworkPackagePage
Vercel AI SDK@memexai/sdk, @memexai/coreVercel AI SDK adapter
Anthropic SDK@memexai/coreAnthropic adapter
LangChain@memexai/sdk, @memexai/coreLangChain adapter
OpenAI SDK@memexai/sdkOpenAI adapter

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