
Read markets and liquidity metrics in Python, maintain CLOB streams and add trading only when needed.
- Language Python
Find your toolkit
A client library helps your code work with a documented interface. Select it for the data, account operation or research task you need, rather than assuming every Polymarket SDK covers the same services.
Check the methods you intend to call and the API behind each one. A library for one service or action may not cover market discovery, historical data and trading together. Compare language support with your application’s runtime and deployment requirements.
Downloading a library supplies code, not automatic access to a hosted dataset or permission to trade. Keep API access and signing permissions separate from package installation. Choose a CLI for command-line work or an MCP server when the intended caller is an assistant.

Read markets and liquidity metrics in Python, maintain CLOB streams and add trading only when needed.

Filtered WebSockets, wallet history, market metadata and order-book data with explicit account-level limits.

Query historical books at 250 ms intervals or replay supported crypto strategies with depth-based fills.

Replay historical Polymarket data in NautilusTrader, compare parameters and inspect portfolio and execution reports.

A professional terminal and signed API for multi-venue orders, fills, positions and strategy PnL.

Develop agent strategies with research, paper trading, replay and supported live integrations.

Daily Parquet market history with event-level books, on-chain fills and separate licensing for commercial use.

A DeFi agent platform with reusable strategies, a continuous execution layer and documented Polymarket endgame workflows.

Integrate order actions, matching and market-making tools through shared API and WebSocket infrastructure.

Combine data clients, wallet tracking and strategy examples in a third-party TypeScript toolkit.

Normalized prediction-market data, matched contracts, replay and paper trading for multi-venue research.

Connect market data, retrieved research and model prompts in an official Python framework that needs development work.