PolyBot

Open-source automated trading system for prediction markets

Documentation | Quick Start | Strategies | Discord

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Trade smarter on Polymarket, Kalshi, and other prediction markets with 10 battle-tested strategies, real-time analytics, and a plugin system for your own AI models.

New: AI Agent Integration - PolyBot now includes an MCP server for AI agents, a Claude Code skill (/polybot), and strategy assessment tools. Let AI analyze your strategies and execute trades with full safety controls.

Why PolyBot?

Feature	PolyBot	Others
Strategies	10 built-in	1-3 typically
Multi-Venue	Polymarket, Kalshi, Binance	Single venue
AI Integration	Plugin system for any model	Hardcoded or none
MCP Server	Full AI agent integration	None
Claude Code Skill	/polybot commands	None
Dashboard	Vue.js real-time UI	Terminal or none
License	MIT	Often GPL or closed

Built for Traders

• Shadow Mode: Test strategies without risking capital
• Risk Controls: Position limits, daily loss limits, exposure caps
• Real-time P&L: Track performance across all positions
• Whale Tracking: Follow successful traders automatically

Built for Developers

• Clean Abstractions: Extend with custom strategies, venues, or AI models
• Type-Safe: Full type hints, Pydantic models, mypy strict
• Well Documented: Comprehensive guides and API reference
• Production Ready: Docker, Prometheus metrics, structured logging

Quick Start

Install from PyPI

pip install polybot-trader

Configure Credentials

# Copy the environment template
cp .env.example .env

# Edit .env with your Polymarket wallet credentials
# Required: POLYMARKET_PRIVATE_KEY, POLYMARKET_PROXY_ADDRESS

Start Trading (Shadow Mode)

# Initialize databases
polybot db init

# Enable a strategy in shadow mode (no real trades)
polybot strategy enable arbitrage
polybot strategy shadow arbitrage --enable

# Start all services
polybot start

Access the dashboard at http://localhost:8000/ui

Docker Deployment

docker compose up -d

Strategies

PolyBot includes 10 trading strategies for prediction markets:

Strategy	Description	Risk Level
Arbitrage	Buy YES + NO when combined price < $1	Low
Statistical Arbitrage	Trade correlated markets that diverge	Medium
AI Model	ML/LLM-predicted probability mispricing	Medium
Spread Farming	Provide liquidity, capture bid-ask spread	Low
Copy Trading	Mirror successful whale traders	Medium
Resolution Arb	Near-expiry mispricing opportunities	Low
Calendar Spread	Time-based price discrepancies	Medium
Momentum	Trend-following on price movements	High
Poll Divergence	Trade when polls diverge from prices	Medium
Volume Spike	React to unusual volume patterns	High

Full strategy documentation

Extending PolyBot

PolyBot is designed for extensibility. Add your own strategies, venues, or AI models.

Custom Strategy

from polybot.strategies.base import BaseStrategy, StrategyConfig
from polybot.models.messages import PriceUpdate, Signal, SignalAction

class MyStrategy(BaseStrategy):
    name = "my_strategy"
    description = "My custom trading strategy"
    
    def _get_config(self) -> StrategyConfig:
        return StrategyConfig(max_position_size=100.0)
    
    async def scan(self, update: PriceUpdate) -> list[Signal]:
        # Your alpha logic here
        if self._found_opportunity(update):
            return [Signal(
                strategy=self.name,
                market_id=update.market_id,
                token_id=update.token_id,
                action=SignalAction.BUY_YES,
                price=update.ask,
                size=50.0,
                reason="Custom signal",
            )]
        return []
    
    async def should_exit(self, position, update) -> bool:
        # Exit logic
        return position.unrealized_pnl_pct > 0.10

AI Model Plugin

from polybot.plugins.base import AIModelPlugin, MarketContext, Prediction

class MyAIPlugin(AIModelPlugin):
    name = "my_ai"
    version = "1.0.0"
    
    async def initialize(self, config: dict) -> None:
        self.model = load_my_model(config["model_path"])
    
    async def predict(self, context: MarketContext) -> Prediction:
        prob = self.model.predict(context.question)
        return Prediction(
            yes_probability=prob,
            confidence=0.8,
            reasoning="Model analysis"
        )
    
    async def should_update(self) -> bool:
        return False

Developer Guide

AI Agent Integration

PolyBot includes comprehensive AI agent integration via MCP (Model Context Protocol):

• MCP Server for AI agents (Claude, etc.) to interact with trading
• Strategy Assessment for AI to analyze and improve strategies
• Claude Code Skill for direct CLI interaction

Quick Start

# Enable MCP server
export MCP_ENABLED=true
export MCP_AI_TRADING_MODE=shadow  # Start with paper trading

# Start MCP server
polybot mcp start

Claude Code Skill

Install the skill for direct CLI access in Claude Code:

cp -r .claude/skills ~/.claude/skills/

Then use /polybot in Claude Code:

/polybot strategy list
/polybot mcp status

AI Capabilities

Feature	Description
Market Analysis	Query markets, prices, positions
Shadow Trading	Paper trade without real money
Live Trading	Real orders with approval workflow
Strategy Assessment	Analyze performance, suggest improvements
CLI Execution	Run polybot commands programmatically

Trading Modes

Mode	Description
disabled	AI can only read market data
shadow	AI can paper trade (no real money)
live	AI can submit real orders (with approval)

Safety Controls

• Position Limits: AI trades limited to MCP_MAX_POSITION_USD
• Daily Loss Limit: Auto-disable if MCP_DAILY_LOSS_LIMIT_USD exceeded
• Approval Queue: Live trades require human approval by default
• Audit Logging: All AI actions logged for review
• CLI Whitelist: Only safe commands allowed via MCP

AI Integration Guide

Architecture

                    Vue.js Dashboard
                          |
                          v
        +-----------------------------------+
        |    FastAPI + WebSocket Gateway    |
        +-----------------------------------+
               |         |         |
               v         v         v
        +---------+ +---------+ +---------+
        | Scanner | |Executor | |Analytics|
        | Service | | Service | | Service |
        +---------+ +---------+ +---------+
               |         |         |
               +---------+---------+
                         |
                         v
        +-----------------------------------+
        |        Strategy Services          |
        |   (10 strategies, AI plugins)     |
        +-----------------------------------+

Services communicate via NNG (nanomsg-next-gen) for high-performance internal messaging.

CLI Reference

# Service management
polybot start              # Start all services
polybot api                # Run API server only
polybot scanner            # Run scanner only
polybot executor           # Run executor only

# Strategy management
polybot strategy list              # List all strategies
polybot strategy enable <name>     # Enable a strategy
polybot strategy disable <name>    # Disable a strategy
polybot strategy shadow <name>     # Toggle shadow mode
polybot strategy run <name>        # Run single strategy

# AI model tools
polybot ai plugins                 # List AI plugins
polybot ai predict <market_id>     # Test prediction
polybot ai scan                    # Scan for opportunities

# MCP (AI Agent) management
polybot mcp start                  # Start MCP server
polybot mcp status                 # Show status and pending approvals
polybot mcp mode <mode>            # Set AI trading mode
polybot mcp pending                # List pending approvals
polybot mcp approve <id>           # Approve AI trade
polybot mcp reject <id>            # Reject AI trade
polybot mcp audit                  # View AI action audit log

# Database
polybot db init            # Initialize databases
polybot db stats           # Show performance stats

# Configuration
polybot config             # Show current config
polybot auth               # Manage API credentials

Documentation

• Installation Guide
• Configuration Reference
• Strategy Deep Dives
• Building Custom Strategies
• AI Plugin Development
• Docker Deployment
• API Reference

Comparison with Alternatives

Feature	PolyBot	Fully-Autonomous AI Bot	OctoBot Prediction	Poly-Maker
Strategies	10 built-in	AI-only	Copy + Arb	Market Making
Multi-venue	Yes (3 venues)	No	No	No
Dashboard	Vue.js real-time	Terminal only	OctoBot UI	Google Sheets
AI plugins	Any model	GPT-4/Claude/Gemini	Via OctoBot	None
MCP Server	Yes - Full integration	No	No	No
Claude Code Skill	Yes - /polybot	No	No	No
CLI Tools	50+ commands	Limited	Via OctoBot	Basic
AI Trading Modes	3 (disabled/shadow/live)	Live only	N/A	N/A
Approval Workflow	Yes - Human-in-loop	No	No	No
Audit Logging	Full AI action logs	Basic	Basic	None
Shadow Mode	Yes	No	Yes	No
License	MIT	MIT	GPL-3.0	MIT

Why PolyBot for AI-Assisted Trading?

PolyBot is the only prediction market trading system with native AI agent support:

• MCP Server: AI agents (Claude, GPT, etc.) can query markets, analyze strategies, and execute trades via the Model Context Protocol
• Claude Code Skill: Run polybot commands directly in Claude Code with /polybot strategy list
• Strategy Assessment: AI can analyze your strategy performance and suggest code improvements
• Safety First: Three trading modes (disabled/shadow/live), approval workflows, position limits, and full audit logging
• 50+ CLI Commands: Complete system control from the command line, all accessible to AI agents

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

# Development setup
git clone https://github.com/cryptuon/polybot
cd polybot
uv sync --dev
uv run pytest

# Run linting
uv run ruff check src/ tests/
uv run mypy src/polybot/

License

MIT License - see LICENSE for details.

Disclaimer

This software is for educational and research purposes. Trading on prediction markets involves financial risk. Use at your own discretion. Not financial advice.

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