
Add schedules, live scores, sportsbook odds, player props and supported fair-price analysis to a sports research application.
- Access API · MCP
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Connect assistants to Polymarket research and data through MCP servers. Compare available tools, hosting requirements and credential boundaries.
Distinguish free public queries, paid data requests and tools that can sign real orders.

Add schedules, live scores, sportsbook odds, player props and supported fair-price analysis to a sports research application.

Compare Polymarket sports prices with profitable-wallet positions, inspect trader grades and track large trades through a dashboard or API.

Research Polymarket, place orders and run scheduled wallet automations through a conversational agent or a connected AI client.

Compare sports prices with money-flow, wallet, analyst and model signals, or query the same game research through a free MCP server.

Inspect resolution-source quality, catalysts and cross-venue question links through a public reference API and MCP server.

Retrieve batch market data and historical order books across prediction venues and options markets for execution research and model testing.

Check whether Polymarket and Kalshi contracts settle the same way before comparing their prices.

Compare wallets or custom trader groups, score positions and receive alerts in the app or Telegram.

Use a common Python interface for prediction-market discovery, orders, positions and streaming, with optional MCP access.

Access normalized prediction-market listings, trades, quotes, order books and historical candles through REST, JSON-RPC or MCP.

Read source-linked prediction-market research, compare model probabilities with prices and access the analysis through reports, API, MCP or a trading CLI.

Practice with a $1,000 virtual bankroll and use a journal to review your decisions.