πΎ OpenClaw β AI Trading Agent for Hyperliquid
OpenClaw is an AI-powered trading agent that uses LLMs to analyze real-time market data, generate trading decisions, and execute trades on the Hyperliquid decentralized exchange.
Built for automation, low-latency execution, and strategy experimentation, OpenClaw continuously monitors markets, evaluates technical indicators, and manages positions with risk controls.
π Features
- π€ LLM-driven trading decisions (multi-model support)
- π Real-time technical analysis via TAAPI
- β‘ Automated trade execution on Hyperliquid
- π Continuous trading loop with configurable intervals
- π‘οΈ Built-in risk management (TP / SL logic)
- π Tool-calling support for dynamic indicator queries
- π‘ Lightweight API for logs & trade diary
π Table of Contents
- Disclaimer
- Architecture
- Live Agents
- Trading Stack
- Project Structure
- Environment Setup
- Usage
- Tool Calling
- Deployment (EigenCloud)
β οΈ Disclaimer
This project is experimental and unaudited. There is no guarantee of profitability. Use at your own risk.
ποΈ Architecture
See full documentation:
β docs/ARCHITECTURE.md
Architecture diagram:
https://github.com/user-attachments/assets/d8f5110a-6401-42bd-b5f5-b154c7b0a418
π‘ Live Agents
- GPT-5 Pro β Portfolio + Logs (active)
- DeepSeek R1 β paused
- Grok 4 β paused
(Replace with your updated endpoints if needed)
π‘ Trading Stack (Recommended Tools & Infrastructure)
OpenClaw is designed to integrate with a high-performance stack including trading bots, MEV tools, analytics platforms, and low-latency infrastructure.
Using the right stack improves:
- β‘ Execution speed
- π Alpha discovery
- π― Trade accuracy
β‘ Execution Layer
Axiom Trade
- Fast on-chain execution
- Reduced fees (10β30%) β Access
Odin Bot
- Automated strategies
- Low-latency execution β Access
Bloom (Telegram Bot)
- Ultra-fast trading interface β Launch
π Analytics & Alpha
GMGN
- Smart money tracking
- Early token discovery β Explore
π§ Advanced Platforms
Padre
- Advanced execution tools β Open
Polymarket
- Prediction-based trading β Try
π₯οΈ Infrastructure
Low-Latency VPS (New York Recommended)
- Faster transaction propagation
- Better execution reliability
- Ideal for bots & MEV strategies
β Get VPS
π Project Structure
src/
βββ main.py # Entry point / trading loop
βββ agent/
β βββ decision_maker.py # LLM decision engine
βββ indicators/
β βββ taapi_client.py # TAAPI integration
βββ trading/
β βββ hyperliquid_api.py # Trade execution
βββ config_loader.py # Env config loader
βοΈ Environment Setup
Create .env (see .env.example):
TAAPI_API_KEY=
HYPERLIQUID_PRIVATE_KEY=
OPENROUTER_API_KEY=
LLM_MODEL=
Optional:
OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
API_PORT=3000
βΆοΈ Usage
poetry run python src/main.py --assets BTC ETH --interval 1h
π Local API
/diaryβ trade history/logsβ runtime logs
π§ Tool Calling
Supports dynamic indicator fetching via TAAPI:
- EMA
- RSI
- Custom indicators
βοΈ Deployment (EigenCloud)
Run inside a TEE (Trusted Execution Environment) for secure key handling.
Install
curl -fsSL https://eigenx-scripts.s3.us-east-1.amazonaws.com/install-eigenx.sh | bash
Deploy
eigenx app deploy
Monitor
eigenx app logs --watch
β οΈ Notes
- Tools listed are optional
- Performance depends on latency + strategy quality
- Always test before scaling