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End-to-end in 5 minutes. By the end you’ll have a memory ingested and retrieved via vector search.

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1. Install

npm install @xtraceai/memory
Node 18 or newer. Works in the browser too.

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2. Get credentials

Sign in at app.xtrace.ai and grab two values from Settings → API Keys:
ValueLooks like
API keyxtk_…
Org idorg_… (or any short string)
Both are required on every request — the API key alone is not sufficient. See Authentication for the full credential setup, including storage best practices.

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3. Ingest a memory

import { MemoryClient } from '@xtraceai/memory';

const client = new MemoryClient({
  apiKey: process.env.XTRACE_API_KEY!,
  orgId:  process.env.XTRACE_ORG_ID!,
});

const job = await client.memories.ingest({
  messages: [
    { role: 'user', content: 'My favorite food is pad see ew. I love Thai cuisine.' },
    { role: 'assistant', content: 'Got it — pad see ew noted.' },
  ],
  user_id: 'alice',
  conv_id: 'conv_2026_05_16',
});

console.log('Ingest job:', job.id, 'status:', job.status);
The call returns immediately with a job in status: "pending" or "running". Extraction runs server-side (3–10 seconds typical).

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4. Wait for extraction to finish

const done = await client.memories.jobs.pollUntilDone(job.id);
console.log('Memories created:', done.result?.memories_created);
The SDK’s pollUntilDone helper handles exponential backoff (500ms → 5s) and a configurable timeout. You can also opt into synchronous mode by passing { wait: true } on ingest — the server holds the connection up to 30 seconds. See Ingesting memories for the full pattern.

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5. Search the memory back

const results = await client.memories.search({
  query: 'what does the user like to eat?',
  user_id: 'alice',
  limit: 5,
});

for (const m of results.data) {
  console.log(m.score?.toFixed(2), '·', m.text);
}
// 0.87 · User loves Thai cuisine.
// 0.82 · User's favorite food is pad see ew.

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What’s next