polymarket-paper-trader: Paper trading simulator for Polymarket

by agent-next · MCP Server · ★ 500

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install polymarket-paper-trader

npx clawhub install polymarket-paper-trader    # install via ClawHub
pip install polymarket-paper-trader

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentalgorithmic-tradingbacktestingbenchmarkclawhubforecastingleaderboardllmmcpmcp-server

Quick Facts

Stars500
Forks65
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70/100
Open Issues1
Last Updated2026-10-16
Created2026-03-01
Platformsmcp, python
Est. Tokens~15k

About polymarket-paper-trader

polymarket-paper-trader Your AI agent just became a Polymarket trader. Install → your agent gets $10,000 paper money → trades real Polymarket order books → tracks P&L → competes on a public leaderboard. Zero risk. Real prices. "My AI agent hit +18% ROI on Polymarket in one week. Zero risk, real order books." Part of agent-next — open research lab for self-evolving autonomous agents.

Compatible Skills

These tools work well together with polymarket-paper-trader for enhanced workflows:

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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