ASI:BlockAgent

A cutting-edge AI-powered system that detects and analyzes large cryptocurrency deposits ("whale activity") on Hyperliquid in real-time, providing traders with instant intelligence about market-moving events.

🎯 What It Does

• Real-Time Whale Detection : Monitors Ethereum mainnet for large deposits (>$100k) to the Hyperliquid bridge using Blockscout MCP integration
• Instant Position Analysis : Automatically fetches whale trading positions, leverage, and liquidation prices from Hyperliquid APIs
• AI-Powered Chat Interface : Natural language queries like "Show me recent whales" or "What positions do large traders have?"
• ASI:ONE Integration : Connects to Agentverse agents for advanced AI capabilities with fallback to local processing

🔧 Technical Architecture & Implementation

Core Technologies Stack

• Frontend : Next.js 14 with TypeScript, Tailwind CSS, Lucide React icons
• Backend : Python with uAgents framework for multi-agent orchestration
• Blockchain Integration : Blockscout MCP (Model Context Protocol) for Ethereum monitoring
• AI Integration : ASI:ONE protocol connecting to Agentverse agents
• APIs : Direct integration with Hyperliquid's trading APIs

Multi-Agent System Design

1. Local Mailbox Agent ( whale_agent_mailbox.py )

• Built with uAgents framework running on port 8001
• Implements two core tools:
  • get_recent_whales() : Queries Blockscout MCP for large bridge deposits
  • enrich_wallet() : Fetches position data from Hyperliquid APIs
• Handles natural language processing for whale detection queries

1. HTTP Server Agent ( whale_agent_http_server.py )

• FastAPI server on port 8002 providing REST endpoints
• Bridges between the frontend and the mailbox agent
• Enables stateless operation without database persistence

1. ASI:ONE Integration ( asi-one.ts )

• Custom TypeScript client for ASI:ONE protocol
• Implements agent discovery and message routing
• Fallback mechanism: tries ASI:ONE first, then local agents

Blockchain Monitoring Innovation

Blockscout MCP Integration :

# Custom MCP client for real-time whale detection
async def get_recent_whales(threshold_usd: float = 100000, lookback_minutes: int = 60):
    # Query Hyperliquid bridge contract: 0x2Df1c51E09aECF9cacB7bc98cB1742757f163dF7
    # Decode deposit events using verified ABI
    # Filter transactions above threshold

Particularly Hacky & Notable :

1. Stateless Architecture : No database! Everything processes live data from APIs
2. Hybrid Agent Routing : Frontend intelligently routes between local and cloud agents based on preferLocal setting
3. Real-time Bridge Monitoring : Direct integration with Blockscout's MCP to catch whale deposits as they happen

Frontend Architecture

Chat Interface ( chat-interface.tsx ):

• React hooks for real-time message streaming
• Dual-mode operation: local vs ASI:ONE agents
• Connection status monitoring with automatic fallbacks
• Quick action buttons for common queries