Prediction Markets Quant for LangChain
com.predictionmarketspicks/quant
Independent quant layer: fee-adjusted edge, Kelly, combos, best price: Kalshi, Polymarket US, Novig
client:LangChain
transport:streamable-http
tools:41
Install Prediction Markets Quant in LangChain
pip install langchain-mcp-adapters
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"quant": {
"transport": "streamable_http",
"url": "https://predictionmarketspicks.com/api/mcp/mcp?via=registry",
}
})
tools = await client.get_tools()
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs
What LangChain can do once it is connected
- fed_rate_odds
- calculate_ev
- kelly_size
- bayes_update
- convert_probability
- stress_test_strategy
- base_rate_gap
- combo_edge
- nfl_power_ratings
- nfl_win_probability
- find_arbitrage
- market_pulse
- commodity_edge
- edge_alerts
- nfl_edge
- nfl_prop_edge
- nhl_edge
- nfl_prop_board
- nba_prop_board
- nba_game_board
- nba_injury_impact
- nfl_ladder
- ladder_arb
- fifteen_min_board