Skip to main content

Atlas API

The Atlas Cognitive Memory API gives AI agents persistent, queryable memory across three cognitive layers: episodic, semantic, and working.
Base URL: https://api.atlas.bsyncs.com

Authentication

All endpoints (except /brain/health) require your API key in the header:
X-API-Key: atlas_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Get your key from the dashboard under API Keys → New key.
Never expose your API key in frontend code or public repositories. Always call Atlas from your backend or a server-side function.

Namespace isolation

The user_id field in request bodies is always overridden server-side from your API key’s namespace. You cannot access another organisation’s data by supplying a different user_id. Your API key → resolves to → org_namespace: acme_corp_a1b2c3 user_id in body → ignored / overridden server-side Use session_id for per-user or per-conversation isolation within your org:
{
  "text": "Alice prefers dark mode.",
  "user_id": "ignored",
  "session_id": "user-alice-uuid"
}

Error format

All errors return:
{
  "detail": "Human-readable error message"
}
CodeMeaning
400Bad request — missing or invalid field
401Invalid or revoked API key
422Validation error — wrong field type
429Rate limit or monthly ops quota exceeded
503Models still loading — retry in 60s
500Internal server error

Rate limits

PlanrpmOps / month
Free101,000
Starter6050,000
Pro300500,000
Scale1,0005,000,000
One operation = one /brain/ingest or one /brain/retrieve call.
/brain/health, /brain/stats, and /brain/consolidate do not count.

Cold start

On first boot, Atlas loads two ML models (Qwen 0.5B + MiniLM). During loading, all brain endpoints return 503. Poll /brain/health until "models_loaded": true before sending requests.
import time, requests

def wait_until_ready(base_url, timeout=120):
    for _ in range(timeout // 5):
        r = requests.get(f"{base_url}/brain/health").json()
        if r.get("ready") and r.get("models_loaded"):
            return True
        time.sleep(5)
    raise TimeoutError("Atlas did not become ready in time")

SDK quickstart

pip install bsyncs-atlas-memory
from atlas_memory import CognitiveBrain

brain = CognitiveBrain(
    api_key="atlas_your_key_here",
    base_url="https://api.atlas.bsyncs.com",
    user_id="user-123",
)

brain.add("Project Apollo uses PostgreSQL on AWS RDS.")
results = brain.search("What database does Apollo use?")
print(results.context)