A
agent-next/polymarket-paper-trader
Paper trading simulator for Polymarket
View on GitHub ↗Link checked 2026-11-12 · automated check blocked (HTTP 429), status unconfirmed
Install & config
Client config (built from the install command this repo gives)
{
"mcpServers": {
"agent-next-polymarket-paper-trader": {
"command": "npx",
"args": ["clawhub"]
}
}
}Parsed from the README we fetched on 2026-11-04; we have not executed it.
command/args come from the install command the repository states. When it is ambiguous, the project README wins.
VS Code (.vscode/mcp.json - the key is servers)
{
"servers": {
"agent-next-polymarket-paper-trader": {
"command": "npx",
"args": ["clawhub"]
}
}
}Same server, but VS Code keeps it under <code>servers</code>.
Claude Code (command line)
claude mcp add --transport stdio agent-next-polymarket-paper-trader -- npx clawhub
Claude Code does not read a config file; add the server with this command.
Key names differ by client: Clients & CLI
- Source
- collected from the abordage/awesome-mcp list · type: MCP server
- Harvest history
- first seen 2026-11-05 · last seen 2026-11-14 · seen 10× · listed by 10 sources
- Score
- score 1,003 · 10 sources · mcp
- Install
npx clawhub
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
npx clawhub. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-11-05；last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.
# 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
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