Your AI tools have
different brains.

curl -X POST http://localhost:8000/sessions \
  -H "Authorization: Bearer sk-..." \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "alice",
    "conversation": "User: I prefer async Python and deploy on Fly.io\nAssistant: Got it.",
    "source_client": "my-app"
  }'

# Response: 202 Accepted — extraction runs in background
{
  "session_id": "uuid",
  "status": "accepted"
}

curl "http://localhost:8000/memory?user_id=alice&q=deployment" \
  -H "Authorization: Bearer sk-..."

# Response
{
  "user_id": "alice",
  "fragments": [
    {
      "content": "User deploys on Fly.io",
      "type": "decision",
      "importance": 4,
      "score": 0.89
    }
  ],
  "prompt_block": "Relevant context about this user:\n- [decision] User deploys on Fly.io (relevance: 0.89)"
}

import httpx, anthropic

async def chat(user_id, message):
    # 1. Fetch memory
    mem = httpx.get(
        "http://localhost:8000/memory",
        params={"user_id": user_id, "q": message},
        headers={"Authorization": "Bearer sk-..."}
    ).json()

    # 2. Inject into system prompt — one line
    system = f"You are helpful.\n\n{mem['prompt_block']}"

    # 3. Call LLM — nothing else changes
    reply = anthropic.Anthropic().messages.create(
        model="claude-opus-4-6", system=system,
        messages=[{"role": "user", "content": message}]
    ).content[0].text

    # 4. Save conversation
    httpx.post("http://localhost:8000/sessions",
        json={"user_id": user_id, "conversation": f"User: {message}\nAssistant: {reply}"},
        headers={"Authorization": "Bearer sk-..."})
    return reply

# Two apps. One ContextOS server. One brain.
# App 1: Claude app writes Alice's memory
import httpx

claude_app = httpx.Client(
    base_url="http://localhost:8000",
    headers={"Authorization": "Bearer sk-claude-app"}
)

# Alice tells your Claude app she prefers async Python
claude_app.post("/sessions", json={
    "user_id": "alice",
    "conversation": "User: I always use async Python and deploy on Fly.io\nAssistant: Got it."
})

# App 2: GPT app reads Alice's memory — written by the Claude app
gpt_app = httpx.Client(
    base_url="http://localhost:8000",
    headers={"Authorization": "Bearer sk-gpt-app"}
)

mem = gpt_app.get("/memory", params={
    "user_id": "alice",
    "q": "what does alice prefer?"
}).json()

# → "Relevant context: [preference] User prefers async Python. Deploys on Fly.io."
# Alice never re-introduced herself. Your GPT app already knows her.
print(mem["prompt_block"])