SDKs
TypeScript SDKs
Use @memexai/sdk for the service or @memexai/core as an in-process runtime.
MemexAI has two TypeScript packages:
@memexai/sdkis the recommended TypeScript service client for the containerized MemexAI service.@memexai/coreis the advanced direct Postgres runtime.
Service SDK
npm install @memexai/sdkimport { 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/coreimport { 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:
| Framework | Package | Page |
|---|---|---|
| Vercel AI SDK | @memexai/sdk, @memexai/core | Vercel AI SDK adapter |
| Anthropic SDK | @memexai/core | Anthropic adapter |
| LangChain | @memexai/sdk, @memexai/core | LangChain adapter |
| OpenAI SDK | @memexai/sdk | OpenAI adapter |