In this guide, you'll fetch real-time on-chain intelligence and integrate it into an AI agent within minutes.
By the end, you will be able to:
Query token data (price, indicators, smart money flow)
Use the data inside an AI workflow
Build a foundation for trading, risk or analytics agents
Setup Guide
Prerequisites
Basic understanding of APIs
curl, Node.js, or Python
Optional: an AI agent or LLM setup
Step 1 : Get Access
Option A - x402 (Recommended)
Use x402 with USDC for per-request payments - no API key required.
Fast setup, instant access, and ready-to-use integration.
Ideal for autonomous agents.
Option B - API Key
To get access to your API key, please send a request to [email protected] or contact us via Discord for faster assistance.
Step 2 : Make Your First Request
Example: Token Intelligence
Example Response
What this provides
Price and technical indicators
Smart money flow insights
Confidence score for AI-driven decisions
Step 3 : Use in an AI Agent
DappLooker provides the data layer. Your AI model provides the reasoning layer.
Quick Example (Node.js)
Architecture Overview
DappLooker acts as the real-time data engine powering your agent.
const query = "Is ETH bullish right now?";
const response = await fetch(
"https://api.dapplooker.com/v1/crypto-market?token_tickers=ETH"
);
const data = await response.json();
// Pass `data` into your LLM for reasoning