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Choose your path. Add a complete UI component to your frontend or add a powerful context layer to your backend.

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Drop-in UI Component

The fastest way to get a full-featured chatbot running in your app. 
// 1. Install the React SDK
// npm install @jeanmemory/react

// 2. Add the provider and complete chat component
import { JeanProvider, JeanChatComplete } from '@jeanmemory/react';

function MyPage() {
  return (
    <JeanProvider apiKey="jean_sk_your_key">
      <JeanChatComplete />
    </JeanProvider>
  );
}

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Headless Backend

For developers who want to power their existing AI agents with our headless SDK. 
# 1. Install the Python SDK
# pip install jeanmemory openai

# 2. Get context before calling your LLM
import os
from jeanmemory import JeanMemoryClient
from openai import OpenAI

jean = JeanMemoryClient(api_key=os.environ["JEAN_API_KEY"])
openai = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

context = jean.get_context(
    user_token="USER_TOKEN_FROM_FRONTEND",
    message="What was our last conversation about?"
).text

prompt = f"Context: {context}\\n\\nUser question: What was our last conversation about?"

# 3. Use the context in your LLM call
completion = openai.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": prompt}]
)
Full-Stack Integration: User signs in with React SDK, then the same user token works across all SDKs. Frontend handles auth, backend gets context.

Don't like reading docs?

Just copy and paste our full documentation into your AI agent (Cursor, Claude, etc.) and tell it what you want to build.
Want to test different depth levels interactively? Check out our Memory Playground with working code examples and live performance comparisons.
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