Open-source prediction market bots give you full transparency, zero recurring fees, and unlimited customization. You can inspect every line of code, verify security practices, and modify strategies to fit your exact needs. The trade-off: they require technical setup and ongoing maintenance.
This guide ranks the best open-source bots and tools available on GitHub in 2026 for Polymarket and Kalshi.
For commercial bot options, see Best Prediction Market Bots 2026. For the full comparison of open-source vs commercial approaches, see Open-Source vs Commercial Bots.
Quick Rankings
| Rank | Project | Platform | Strategy | Language | Ease of Setup |
|---|---|---|---|---|---|
| 1 | Kalshi News Bot | Kalshi | Sentiment + auto-trade | Python | Easy |
| 2 | PolyClaw | Polymarket | Arb + hedge discovery | Python | Moderate |
| 3 | Polyseer | Polymarket + Kalshi | Research + Bayesian | Python | Moderate |
| 4 | OctoBot | Multi-platform | Multi-strategy | Python | Moderate |
| 5 | py-clob-client | Polymarket | SDK (build your own) | Python | Easy |
| 6 | polymarket-cli | Polymarket | CLI (build your own) | Rust | Easy |
Detailed Reviews
1. Kalshi News Bot
Platform: Kalshi | Strategy: News sentiment + automated trading | Lines of code: ~300
The Kalshi News Bot is the simplest complete trading bot in the prediction market ecosystem. It uses Claude AI to analyze breaking news, identify mispriced Kalshi events, and place trades automatically.
Strengths:
- Extremely simple codebase (~300 lines) — easy to understand and modify
- Uses Claude for high-quality news analysis
- One-click deploy potential
- Complete trading pipeline: scan → analyze → trade
- Active maintenance
Limitations:
- Kalshi-only (no Polymarket support)
- Requires Anthropic API key (Claude costs apply per request)
- No backtesting framework
- No web dashboard (terminal only)
- No position management beyond entry
Best for: Developers who want a working, understandable trading bot as a starting point. The small codebase makes it ideal for learning how prediction market bots work.
Setup:
git clone <kalshi-news-bot-repo>
pip install -r requirements.txt
# Set KALSHI_API_KEY, KALSHI_PRIVATE_KEY, ANTHROPIC_API_KEY
python bot.py
2. PolyClaw
Platform: Polymarket | Strategy: Arbitrage + hedge discovery | Framework: OpenClaw skill
PolyClaw is an OpenClaw skill that adds Polymarket trading capabilities with a unique feature: LLM-powered hedge discovery via contrapositive logic. Instead of just finding direct arbs, it identifies hedging opportunities across semantically related markets.
Strengths:
- Novel hedge discovery using contrapositive reasoning
- Built on the OpenClaw agent framework (composable with other skills)
- Order execution and book reading via py-clob-client
- Active development and community
Limitations:
- Requires OpenClaw framework setup
- Contrapositive logic can produce false positive hedges
- LLM costs for hedge discovery (requires API key)
- More complex architecture than standalone bots
Best for: Developers building multi-skill agents on the OpenClaw framework who want Polymarket trading capabilities with intelligent hedge discovery.
3. Polyseer
Platform: Polymarket + Kalshi | Strategy: Research + Bayesian probability aggregation
Polyseer is not a trading bot — it is a research platform that uses multi-agent architecture and Bayesian probability aggregation to analyze prediction market events. Multiple AI agents research different aspects of an event, then their probability estimates are aggregated using Bayesian methods.
Strengths:
- Multi-agent research architecture (multiple LLMs analyze in parallel)
- Bayesian probability aggregation (mathematically principled estimate combination)
- Supports both Polymarket and Kalshi events
- Research-focused — provides probability estimates, not trading signals
- Active development
Limitations:
- No trading execution (research only)
- Significant LLM API costs for multi-agent research
- Complex setup with multiple dependencies
- Output quality depends on LLM quality and prompt engineering
Best for: Researchers who want AI-assisted probability estimation before making manual trades, or developers building the intelligence layer of a larger trading system.
4. OctoBot
Platform: Multi-platform | Strategy: Multi-strategy (configurable)
OctoBot is a general-purpose open-source trading bot with community-built plugins for prediction markets. Originally designed for crypto trading, its plugin architecture supports Polymarket and other platforms.
Strengths:
- Mature codebase with years of development
- Visual configuration interface (web dashboard)
- Multiple strategy plugins: arb, market making, momentum, DCA
- Backtesting framework included
- Active community with regular updates
Limitations:
- Prediction market support is via community plugins (not core)
- General-purpose design means less prediction-market-specific optimization
- Heavier setup than single-purpose bots
- Premium features behind paid tier ($49-99/mo)
Best for: Traders who want a mature, multi-strategy framework and are comfortable with plugin-based architecture.
5. py-clob-client (Official Polymarket SDK)
Platform: Polymarket | Strategy: Build your own
The official Polymarket Python SDK. Not a bot itself, but the foundation that most Polymarket bots are built on.
Strengths:
- Official, maintained by Polymarket team
- Complete API coverage (all CLOB endpoints)
- Well-documented with type hints
- Production-tested by the platform itself
Limitations:
- SDK only — no trading logic, strategy, or bot framework
- You build everything from scratch
- Rate limiting not handled automatically
Best for: Developers who want complete control and are building a custom bot from the ground up. See the py_clob_client Reference for complete documentation.
6. polymarket-cli (Rust CLI)
Platform: Polymarket | Strategy: Interactive trading / scripting
The official Polymarket CLI — a Rust binary for querying markets, placing trades, and managing orders from the terminal.
Strengths:
- Official, maintained by Polymarket
- JSON output mode (
-o json) for scripting and piping - Interactive shell mode (
polymarket shell) - Fast — compiled Rust binary
- No Python environment needed
Limitations:
- CLI tool, not a bot framework
- Scripting requires shell scripting (bash, etc.)
- No built-in strategy logic
Best for: Quick prototyping, debugging, and building shell-based automation. Ideal complement to the Python SDK.
Evaluation Criteria
| Criterion | Weight | What We Assess |
|---|---|---|
| Code quality | 25% | Clean architecture, type hints, error handling, tests |
| Documentation | 20% | README, inline comments, setup instructions, examples |
| Maintenance | 20% | Recent commits, issue response time, release frequency |
| Strategy quality | 20% | Soundness of the trading logic, risk management |
| Ease of setup | 15% | Dependencies, configuration, time to first trade |
Security Checklist for Open-Source Bots
Before running any open-source bot with real funds:
- Read the code — especially wallet/key handling and any outbound API calls
- Use a dedicated wallet — never your main wallet or one with significant funds
- Start small — test with minimum viable amounts
- Check the repo history — look for suspicious recent commits
- Verify dependencies — run
pip auditor similar to check for known vulnerabilities - Watch for forks — malicious forks may look identical but contain hidden changes
- Set spending limits — use Coinbase Agentic Wallets for programmable spending caps
See Also
- Best Prediction Market Bots 2026 — All bots ranked (open-source + commercial)
- Open-Source vs Commercial Bots — Detailed comparison
- Best Polymarket Bots 2026 — Polymarket-specific rankings
- Best Kalshi Trading Bots 2026 — Kalshi-specific rankings
- py_clob_client Reference — Official Polymarket SDK documentation
- Polymarket Trading Bot Quickstart — Build your own from scratch
- Agent Betting Glossary — 130+ prediction market terms defined
- Tool Directory — All tools in the ecosystem
Rankings updated March 2026. Not financial advice. Built for builders.