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polymarket-paper-trader MCP Server

agent-next/polymarket-paper-trader

Score: 64.3 Rank #5203 Database
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Paper trading simulator for Polymarket

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Overview

agent-next/polymarket-paper-trader is a Python MCP server licensed under MIT. Paper trading simulator for Polymarket Topics: ai-agent, algorithmic-trading, backtesting, clawhub, mcp, openclaw, paper-trading, polymarket, prediction-markets, python, sqlite, trading-bot, benchmark, forecasting, leaderboard, llm, mcp-server, model-context-protocol.

Ranked #5203 out of 24846 indexed tools.

Ecosystem

Python MIT
ai-agentalgorithmic-tradingbacktestingclawhubmcpopenclawpaper-tradingpolymarketprediction-marketspythonsqlitetrading-botbenchmarkforecastingleaderboardllmmcp-servermodel-context-protocol

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 498

498 stars → growing community

Freshness 25% 17d ago

Last commit 17d ago → recently updated

Issue Health 25% 29%

2/7 issues closed → many open issues

Contributors 10% 2

2 contributors → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 65
Description Brief
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Issue Health high impact

You have 5 open vs 2 closed issues — triaging stale issues improves health

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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AgentRank score for agent-next/polymarket-paper-trader
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Matched Queries

"mcp server""mcp-server"topic:mcptopic:mcp-servertopic:model-context-protocol

From the README

# polymarket-paper-trader

**A zero-risk gym for AI agents on real prediction markets — real order books, official fees, verified fill fidelity. Practice, evaluate, and benchmark decision intelligence.**

Agents make probability judgments all day. Polymarket is the world's largest prediction market, and its order books are the honest scoreboard: real money, real prices, real outcomes. But you cannot hand an agent a wallet to learn with. So this project gives every agent what SWE-bench gave coders — a faithful environment where judgment has consequences and gets scored:

- **Practice** — your agent trades $10k of paper money against live Polymarket order books, with the same fee model and fill mechanics as the real exchange
- **Evaluate** — the `polymarket-benchmark` harness in this repository (installed separately) scores any model on prediction-market decision sets (Brier score, calibration, alpha)
- **Compare** — multi-account battles and leaderboards rank agents against each other
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Read full README on GitHub →

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