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@lazymac/polymarket-intel-mcp

v0.1.0

Published

Polymarket prediction market intelligence MCP — real-time market data, position analysis, alpha signals from Lumen's PM bot v39.2 (lottery-purge calibrated). Useful for AI agents researching prediction markets, traders building dashboards, or systems anal

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Links

Maintainers

lazymaclazymac

Keywords

mcpmodel-context-protocolpolymarketprediction-markettradingalpha

Readme

Polymarket Intel MCP

Polymarket prediction market intelligence for AI agents — real-time market data, lottery-bias filter, alpha signals.

What it does

6 tools for Claude / Cursor / Windsurf / any MCP client:

  • search_markets(query) — keyword search
  • get_market(condition_id|slug) — full market detail
  • market_orderbook(token_id) — orderbook snapshot
  • top_movers(direction) — 24h biggest price movers
  • lottery_filter(min_price, max_price) — Lumen v39.2 lottery-purge filter: only safer 0.20-0.92 zone, excludes 5-20¢ tail traps per CEPR 2026 research on 300K Kalshi contracts
  • portfolio_snapshot(wallet) — public portfolio summary

Why

After running a Polymarket bot for 3 months and learning the hard way that <$0.05 entries lose 69% of capital (28 positions, real data), this MCP encodes those lessons as a filter — and exposes Polymarket's open data so AI agents can analyze prediction markets without scraping.

Install

npm install -g @lazymac/polymarket-intel-mcp

Or via Claude Code:

claude mcp add polymarket-intel --scope user -- npx -y @lazymac/polymarket-intel-mcp@latest

Pricing

  • Free for personal use (no auth required)
  • $19/mo Pro: rate-limit bypass, alpha signal feed, lottery_filter_pro (volume-weighted edge ranking) — coming soon via MCPize

Use cases

  • AI agents researching markets: "Will X happen?" → query Polymarket implied probability
  • Traders: catch top movers, filter long-shot bias
  • Builders: integrate prediction market data into your dashboard

License

MIT. PRs welcome.