What is Polymarket Agents?
Polymarket Agents is an open-source developer framework and set of utilities for building AI agents that trade autonomously on Polymarket β the world’s largest prediction market platform.
This framework enables developers to:
- π€ Build AI agents that analyze markets and execute trades automatically
- π Integrate with Polymarket API for real-time market data
- π Use RAG (Retrieval-Augmented Generation) for informed trading decisions
- π° Source data from betting services, news providers, and web search
- π§ Leverage comprehensive LLM tools for prompt engineering and market analysis
π GitHub: https://github.com/Polymarket/agents
What is Polymarket?
Polymarket is a decentralized prediction market platform where users trade on the outcomes of real-world events:
- Politics β Election results, policy decisions
- Crypto β Bitcoin price predictions, ETF approvals
- Sports β Game outcomes, championship winners
- Science β Research breakthroughs, space missions
- Entertainment β Award winners, box office results
Traders buy “Yes” or “No” shares based on their predictions, with prices reflecting the market’s consensus probability.
Key Features
| Feature | Description |
|---|---|
| Polymarket API Integration | Full access to market data, order book, and trade execution |
| AI Agent Utilities | Tools for building autonomous trading agents |
| Local & Remote RAG | Vector database support for news and market data retrieval |
| Multi-Source Data | Betting services, news APIs, web search integration |
| LLM Prompt Engineering | Comprehensive tools for context-aware reasoning |
| CLI Interface | Command-line tool for market analysis and trading |
| Docker Support | Containerized deployment for easy setup |
| MIT License | Free and open-source |
Architecture
Polymarket Agents features modular components that can be maintained and extended by the community:
Core APIs
| Component | Purpose |
|---|---|
| Chroma.py | Vector database for news sources and API data |
| Gamma.py | Polymarket Gamma API client for market metadata |
| Polymarket.py | Main API class for market data and trade execution |
| Objects.py | Pydantic data models for trades, markets, events |
CLI Commands
The primary user interface for interacting with Polymarket:
# Get all markets sorted by volume
python scripts/python/cli.py get-all-markets --limit 10 --sort-by volume
# Get specific market details
python scripts/python/cli.py get-market --market-id <MARKET_ID>
# Execute a trade
python scripts/python/cli.py trade --market-id <MARKET_ID> --side buy --size <SIZE>
Quick Start
1. Clone Repository
git clone https://github.com/polymarket/agents.git
cd agents
2. Set Up Environment
# Create virtual environment
virtualenv --python=python3.9 .venv
source .venv/bin/activate
# Install dependencies
pip install -r requirements.txt
3. Configure API Keys
Create .env file:
POLYGON_WALLET_PRIVATE_KEY="your-wallet-private-key"
OPENAI_API_KEY="your-openai-api-key"
4. Load Wallet with USDC
Transfer USDC to your Polygon wallet for trading.
5. Run CLI
# Set Python path
export PYTHONPATH="."
# Run CLI
python scripts/python/cli.py
Or execute trades directly:
python agents/application/trade.py
6. Docker Alternative
./scripts/bash/build-docker.sh
./scripts/bash/run-docker-dev.sh
Trading Strategies
Polymarket Agents supports various AI-driven trading strategies:
1. News-Based Trading
- Monitor news sources for event developments
- Use LLM to analyze sentiment and impact
- Execute trades based on predicted outcomes
2. Arbitrage Detection
- Compare prices across related markets
- Identify mispriced probabilities
- Execute risk-free arbitrage trades
3. Trend Following
- Analyze market volume and price movements
- Identify momentum in specific markets
- Ride trends for profit
4. Fundamental Analysis
- Research event background and factors
- Use RAG to query historical data
- Make informed predictions
Data Sources
The framework integrates multiple data sources:
| Source | Type | Use Case |
|---|---|---|
| News APIs | Real-time news | Event tracking |
| Web Search | General information | Background research |
| Betting Services | Odds comparison | Price discovery |
| Social Media | Sentiment analysis | Trend detection |
| On-Chain Data | Transaction data | Market intelligence |
RAG Implementation
Retrieval-Augmented Generation for informed trading:
- Vector Database β Chroma DB stores news articles and market data
- Embedding β Convert text to vectors for semantic search
- Retrieval β Query relevant information based on market context
- Generation β LLM synthesizes retrieved data into trading decisions
Risk Management
Important considerations for automated trading:
| Risk | Mitigation |
|---|---|
| Market Risk | Position sizing, stop-losses |
| Liquidity Risk | Trade in high-volume markets |
| Model Risk | Backtest strategies before live trading |
| Operational Risk | Monitor bot performance regularly |
| Regulatory Risk | Comply with local regulations |
Comparison with Other Tools
| Feature | Polymarket Agents | Custom Bot | Manual Trading |
|---|---|---|---|
| Open Source | β | Varies | N/A |
| AI Integration | β | Optional | β |
| RAG Support | β | Rare | β |
| Multi-Source Data | β | Optional | β |
| CLI Interface | β | Varies | N/A |
| Community | β | Varies | β |
| Speed | Fast | Fast | Slow |
| Emotion-Free | β | β | β |
Use Cases
1. Political Event Trading
- Election outcomes
- Policy decisions
- Legislative votes
2. Crypto Market Predictions
- Bitcoin price movements
- ETF approvals
- Regulatory decisions
3. Sports Betting
- Game outcomes
- Championship winners
- Player performance
4. Entertainment Markets
- Award winners
- Box office predictions
- Reality show outcomes
Related Repositories
| Repository | Purpose |
|---|---|
| py-clob-client | Python client for Polymarket CLOB |
| python-order-utils | Order generation and signing |
| clob-client | TypeScript client for CLOB |
| Langchain | Context-aware reasoning |
| Chroma | Vector database |
Reading Resources
- Prediction Markets: Bottlenecks and Next Unlocks
- Crypto + AI Applications by Vitalik Buterin
- Superforecasting
Related Articles
- 28 Tools Behind a $1M Polymarket Trading Bot: Full Stack Breakdown β Complete trading bot architecture
- Code Vault β 7 Open-Source Crypto Radar & Trading Tools β Python trading automation
- Free Claude Code: Use Claude Code CLI for Free β AI coding assistant
Conclusion
Polymarket Agents provides a solid foundation for building AI-powered trading bots on prediction markets. The modular architecture, comprehensive API integration, and RAG capabilities make it suitable for both beginners and experienced developers.
Best for: Developers interested in algorithmic trading, prediction markets, and AI-driven decision making
GitHub: https://github.com/Polymarket/agents
Last updated: 2026-05-06