Prediction markets have exploded in popularity, and developers are racing to build tools on top of platforms like Polymarket and Kalshi. If you’re looking to integrate real-time market data, automate trading strategies, or create custom dashboards, understanding these APIs is essential. This guide walks you through what each platform offers, how to avoid common pitfalls, and which tools can speed up your development in 2026.
What each API exposes in 2026
Both Polymarket and Kalshi have matured their API offerings significantly. Polymarket‘s API provides access to market metadata, order books, trade history, and user positions. You can query active markets, retrieve price feeds, and pull historical settlement data. Kalshi‘s API similarly exposes market listings, current bid-ask spreads, trade execution endpoints, and account balances. Both platforms support programmatic order placement, making them ideal for algorithmic trading.
Polymarket operates on blockchain infrastructure, so some data lives on-chain and can be queried directly via smart contracts. Kalshi, a CFTC-regulated exchange, centralizes its data but offers robust REST endpoints. Developers should note that Polymarket’s API documentation improved dramatically in late 2025, adding better examples and error-code references.
Rate limits, auth, and gotchas
Kalshi enforces a 100-requests-per-minute limit on public endpoints and 300 for authenticated users. Polymarket’s limits are less strict but vary by endpoint. Authentication on Kalshi uses API keys with HMAC signatures, while Polymarket requires wallet signatures for write operations. Always cache market snapshots locally to avoid hitting rate caps during high-frequency polling.
A common gotcha is timezone handling. Kalshi timestamps are UTC, but Polymarket sometimes returns block timestamps. Test your parsers carefully. Another trap is stale data during market resolution. Both platforms can lag by seconds when outcomes settle, so build retry logic into your code.
REST vs websocket coverage
Kalshi offers websockets for real-time order book updates and trade streams. Polymarket added websocket support in early 2026, covering market creation events and price ticks. REST is fine for dashboards, but bots need websockets to stay competitive. Expect occasional disconnects and implement exponential backoff reconnection strategies.
Common integration patterns: bots, dashboards, alerts
Trading bots typically subscribe to websocket feeds, calculate probabilities, and place limit orders via REST. Dashboards poll market summaries every few seconds and display charts using libraries like Chart.js. Alert systems watch for price thresholds or volume spikes and send notifications via Telegram or email. Many developers combine all three patterns into a single Node.js or Python service.
Open-source clients and SDKs
The community has built several wrappers. The unofficial py-polymarket library simplifies Python integration, while kalshi-node is popular for JavaScript projects. Both are actively maintained on GitHub. Official SDKs are minimal, so these community tools save hours of boilerplate coding. Always verify the library’s last commit date before depending on it.