How to integrate API

How to Integrate KANGAROO AI via API

Introduction

KANGAROO AI provides a powerful API that allows developers to integrate AI-powered trading signals, market analysis, and automated trading execution into their own applications or platforms. This guide will walk you through the process of connecting to the API and executing basic operations.

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1. Getting API Access

To use the KANGAROO AI API, follow these steps:

1. Sign up on the website and create an account.

2. Generate an API key from the developer dashboard.

3. Whitelist your IP address (if required for security).

4. Read the API documentation to understand available endpoints and authentication.

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2. Authentication

The API uses Bearer Token Authentication. Include your API key in the Authorization header of each request.

Example Request (Python):

import requests

API_KEY = "your_api_key_here"
BASE_URL = "https://api.kangaroo.ai"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

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3. Fetching Market Data

Use this endpoint to get real-time market data analyzed by KANGAROO AI.

Endpoint:

GET /market-data

Example Request:

response = requests.get(f"{BASE_URL}/market-data", headers=headers)
print(response.json())

Example Response:

{
    "pair": "SOL/USDC",
    "trend": "bullish",
    "volatility": 3.4,
    "liquidity": 1.2,
    "recommendation": "BUY"
}

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4. Executing a Trade

KANGAROO AI can execute trades on behalf of users based on AI analysis.

Endpoint:

POST /execute-trade

Request Payload:

{
    "pair": "SOL/USDC",
    "order_type": "market",
    "amount": 10,
    "side": "buy"
}

Example Request:

trade_data = {
    "pair": "SOL/USDC",
    "order_type": "market",
    "amount": 10,
    "side": "buy"
}

response = requests.post(f"{BASE_URL}/execute-trade", json=trade_data, headers=headers)
print(response.json())

Example Response:

{
    "status": "success",
    "order_id": "abc123xyz",
    "filled_price": 145.23
}

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5. Checking Order Status

To track the status of an order, use the order ID from the execution response.

Endpoint:

GET /order-status/{order_id}

Example Request:

order_id = "abc123xyz"
response = requests.get(f"{BASE_URL}/order-status/{order_id}", headers=headers)
print(response.json())

Example Response:

{
    "order_id": "abc123xyz",
    "status": "filled",
    "executed_price": 145.23
}

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6. Webhook Integration (Optional)

For real-time notifications on trade executions, you can set up webhooks.

Setting Up a Webhook:

1. Go to the KANGAROO AI Developer Dashboard.

2. Register your webhook URL.

3. Handle incoming POST requests from KANGAROO AI.

Example Webhook Handler (Flask in Python):

from flask import Flask, request

app = Flask(__name__)

@app.route("/webhook", methods=["POST"])
def webhook():
    data = request.json
    print("Received webhook:", data)
    return {"status": "received"}, 200

if __name__ == "__main__":
    app.run(port=5000)

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Conclusion

By integrating KANGAROO AI’s API, you can automate trading, access AI-driven market analysis, and improve your trading efficiency on Solana DEXs. For further details, visit our full API documentation.