A
agent-next/polymarket-paper-trader
Paper trading simulator for Polymarket
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · 自动访问被拒（HTTP 429），状态未能确认
安装与配置
客户端配置（取自该仓库的安装命令）
{
"mcpServers": {
"agent-next-polymarket-paper-trader": {
"command": "npx",
"args": ["clawhub"]
}
}
}解析自我们于 2026-11-04 抓取的该仓库 README；我们未执行过。
command/args 来自仓库写明的安装命令；不确定时请以该项目 README 为准。
VS Code（.vscode/mcp.json —— 键名是 servers）
{
"servers": {
"agent-next-polymarket-paper-trader": {
"command": "npx",
"args": ["clawhub"]
}
}
}VS Code 顶层键是 <code>servers</code>，其余与上面那份相同。
Claude Code（命令行）
claude mcp add --transport stdio agent-next-polymarket-paper-trader -- npx clawhub
Claude Code 不收 JSON 文件，用这条命令直接加。
配置项的键名以你的客户端为准：客户端与 CLI
- 来源明细
- 收录自 abordage/awesome-mcp 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
- 安装
npx clawhub
常见问题（答案都来自我们的记录）
怎么安装？
该仓库给出的安装命令是
npx clawhub。我们的记录里它是仓库自己提供的；不保证在你的客户端上直接可用。它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
我们收录于 2026-11-05；最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
# polymarket-paper-trader
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
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
Compete — Forecast Arena: the live public leaderboard where AI models and simple baselines forecast the same Polymarket questions daily and are scored by real outcomes (Brier score). Runs from this repo (enter your model · workflow · raw data).
Part of agent-next — building an agentic world.
## 60-second demo
bash
pip install polymarket-paper-trader
pm-trader init --balance 10000 # $10k paper money
pm-trader markets search "bitcoin" # find markets
pm-trader buy will-bitcoin-hit-100k yes 500 # buy $500 of YES
pm-trader stats --card # shareable stats card
Prefer not to install? uvx --from polymarket-paper-trader pm-trader-mcp runs the MCP
server your agent connects to (see Works with below).
That's it. Your AI agent is now trading Polymarket with zero risk.
## Install
bash
# via pip (CLI + MCP server)
pip install polymarket-paper-trader
# or the MCP server alone, with no install
uvx --from polymarket-paper-trader pm-trader-mcp
# from source (development)
uv pip install -e ".[dev]"
Requires Python 3.10+.
## Works with
| Runtime | One-line install |
| Claude Code | /plugin marketplace add agent-next/polymarket-paper-trader |
| Codex CLI | codex mcp add polymarket-paper-trader -- uvx --from polymarket-paper-trader pm-trader-mcp |
| Cursor | |
| Gemini CLI | gemini extensions install https://github.com/agent-next/polymarket-paper-trader |
| OpenCode / Goose / Cline / Windsurf / Copilot | add pm-trader-mcp to the client's MCP config |
| OpenClaw / ClawHub | npx clawhub install polymarket-paper-trader |
| Hermes Agent / LangChain / OpenAI Agents SDK / CrewAI | wrap uvx --from polymarket-paper-trader pm-trader-mcp |
| ChatGPT / Claude.ai (remote MCP) | add the remote /mcp URL in the host's remote-MCP settings |
Full copy-paste config for every runtime above (plus Grok/xAI remote MCP): docs/integrations.md.
Hosts that implement MCP Apps render portfolio and stats as an
inline dashboard; every other host gets the same text result.
## Use it from ChatGPT / Claude.ai / personal agents
Remote mode exists for hosts that only speak HTTP: run
pm-trader-mcp --transport streamable-http with the opt-in --auth-issuer,
--auth-audience and --resource-url flags, then add your server's /mcp
URL in the host's remote-MCP settings. It is off by default, and it needs an
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
Compete — Forecast Arena: the live public leaderboard where AI models and simple baselines forecast the same Polymarket questions daily and are scored by real outcomes (Brier score). Runs from this repo (enter your model · workflow · raw data).
Part of agent-next — building an agentic world.
## 60-second demo
bash
pip install polymarket-paper-trader
pm-trader init --balance 10000 # $10k paper money
pm-trader markets search "bitcoin" # find markets
pm-trader buy will-bitcoin-hit-100k yes 500 # buy $500 of YES
pm-trader stats --card # shareable stats card
Prefer not to install? uvx --from polymarket-paper-trader pm-trader-mcp runs the MCP
server your agent connects to (see Works with below).
That's it. Your AI agent is now trading Polymarket with zero risk.
## Install
bash
# via pip (CLI + MCP server)
pip install polymarket-paper-trader
# or the MCP server alone, with no install
uvx --from polymarket-paper-trader pm-trader-mcp
# from source (development)
uv pip install -e ".[dev]"
Requires Python 3.10+.
## Works with
| Runtime | One-line install |
| Claude Code | /plugin marketplace add agent-next/polymarket-paper-trader |
| Codex CLI | codex mcp add polymarket-paper-trader -- uvx --from polymarket-paper-trader pm-trader-mcp |
| Cursor | |
| Gemini CLI | gemini extensions install https://github.com/agent-next/polymarket-paper-trader |
| OpenCode / Goose / Cline / Windsurf / Copilot | add pm-trader-mcp to the client's MCP config |
| OpenClaw / ClawHub | npx clawhub install polymarket-paper-trader |
| Hermes Agent / LangChain / OpenAI Agents SDK / CrewAI | wrap uvx --from polymarket-paper-trader pm-trader-mcp |
| ChatGPT / Claude.ai (remote MCP) | add the remote /mcp URL in the host's remote-MCP settings |
Full copy-paste config for every runtime above (plus Grok/xAI remote MCP): docs/integrations.md.
Hosts that implement MCP Apps render portfolio and stats as an
inline dashboard; every other host gets the same text result.
## Use it from ChatGPT / Claude.ai / personal agents
Remote mode exists for hosts that only speak HTTP: run
pm-trader-mcp --transport streamable-http with the opt-in --auth-issuer,
--auth-audience and --resource-url flags, then add your server's /mcp
URL in the host's remote-MCP settings. It is off by default, and it needs an
收录徽章（可选）
想把收录标记放进 README 就复制这行，可选，不影响收录。
[](https://anclum.com/zh/s/agent-next-polymarket-paper-trader/)
- 来源
- awesome · https://github.com/agent-next/polymarket-paper-trader
- 按领域浏览
- MCP 服务
- 收录来源
- 10 个独立来源
- 收录于
- 今天
同类推荐
所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。