Polymarket Paper Trader

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Simulate prediction market trading using live order books, authentic fee models, and realistic fill execution for AI agents and algorithmic strategies.

Polymarket Paper Trader provides a zero-risk gym for AI agents and quantitative traders looking to interact with live prediction markets. By connecting directly to Polymarket and Kalshi order books, it faithfully replicates market mechanics—including slippage, partial fills, tick sizes, and official match fee curves—without risking real capital. The tool includes a native Model Context Protocol (MCP) server, allowing autonomous agents in platforms like Claude Code, Cursor, and OpenClaw to practice decision-making, manage virtual cash balances, run automated trading strategies, and benchmark forecasting performance against real-world outcomes.

主な機能

01Provides an MCP server interface exposing tools for account management, market discovery, order placement, and portfolio tracking
02Supports multiple prediction market ecosystems, including live Polymarket order books and Kalshi markets
03493 GitHub stars
04Simulates order book depth, slippage, and exact per-match exchange fee schedules for realistic execution fidelity
05Includes strategy backtesting, multi-account A/B testing, and head-to-head competitive battle modes
06Features automated resolution handling that pays out standard contract values upon market closure

ユースケース

01Backtesting and dry-running algorithmic trading bots before deploying real funds on prediction exchanges
02Evaluating and benchmarking LLM decision-making, calibration, and Brier scores against real-world forecasting markets
03Giving autonomous AI coding assistants and agents real-time market research and simulation capabilities via MCP