Quantoracle
About
63 deterministic quant computation tools for autonomous financial agents. Options pricing, derivatives, risk, portfolio optimization, statistics, crypto/DeFi, macro/FX. 1,000 free calls/day, no signup.
Details
- Transport
- SSE
- License
- MIT
Explore
- 63 deterministic, citation-verified financial calculators
- 10 composite workflows for common agent tasks
- Sub-millisecond to
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
QuantoracleCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
curl -X POST https://api.quantoracle.dev/v1/options/price \
-H "Content-Type: application/json" \
-d '{"S": 100, "K": 105, "T": 0.5, "r": 0.05, "sigma": 0.2, "type": "call"}'
{
"price": 4.5817,
"intrinsic": 0,
"time_value": 4.5817,
"breakeven": 109.5817,
"prob_itm": 0.4056,
"greeks": {
"delta": 0.4612,
"gamma": 0.0281,
"theta": -0.0211,
"vega": 0.2808,
"rho": 0.2077,
"vanna": 0.0047,
"charm": -0.0006,
"volga": 0.0327,
"speed": -0.0001
},
"d1": -0.0975,
"d2": -0.2389,
"ms": 12.4
}
npx quantoracle-mcp
curl https://api.quantoracle.dev/usage
options_price
Black-Scholes pricing with 10 Greeks (delta through color). Crypto underlying? Pair with /v1/live/volatility for fresh realized vol instead of a static sigma; perp carry at /v1/live/funding-rates. Use when you need to price a European option or compute Greeks (delta, gamma, theta, vega, rho, etc.) using the Black-Scholes model. Provide spot price, strike, time to expiry, risk-free rate, and volatility. Returns: option price, 10 Greeks, and intrinsic/time value breakdown.
options_implied-vol
Newton-Raphson implied volatility solver. Converges in 5-8 iterations. Use when you know the market price of an option and need to back out the implied volatility. Uses Newton-Raphson iteration. Provide spot, strike, time to expiry, risk-free rate, market price, and option type. Returns: implied volatility, convergence info, and Greeks at that IV.
options_strategy
Multi-leg options strategy P&L, breakevens, max profit/loss, risk/reward. Use when analyzing a multi-leg options strategy (spreads, straddles, iron condors, etc.). Provide an array of legs with strike, premium, quantity, and type. Returns: net premium, max profit/loss, breakeven points, P&L at various prices, and payoff data.
risk_portfolio
22 risk metrics: Sharpe, Sortino, Calmar, Omega, VaR, CVaR, drawdown, skew, kurtosis. Use when you have a series of portfolio returns and need comprehensive risk analytics. Provide an array of periodic returns (e.g. daily). Returns: 22 metrics including Sharpe, Sortino, Calmar, Omega, VaR (95/99), CVaR, max drawdown, skewness, kurtosis, win rate, profit factor. Optionally provide benchmark returns for alpha, beta, tracking error, and information ratio.
risk_kelly
Kelly Criterion: discrete (win/loss) or continuous (returns series) mode. Use when determining optimal bet/position sizing using the Kelly Criterion. Provide win probability and win/loss ratio. Returns: full Kelly fraction, half-Kelly, quarter-Kelly, and expected growth rate.
simulate_montecarlo
GBM Monte Carlo with contributions/withdrawals. Up to 5000 paths. Use when running a Monte Carlo simulation for asset price paths. Provide starting price, drift, volatility, time horizon, and number of simulations. Returns: simulated terminal prices, percentile distribution (5th/25th/50th/75th/95th), expected value, probability of profit, and path statistics. NOTE: Via MCP, keep simulations ≤ 1000 and years ≤ 30 for fastest response. For larger simulations (up to 5000 paths, 100 years), call…
indicators_technical
13 technical indicators + composite signals. Use when you need multiple technical indicators computed from a price series. Provide an array of prices and optional volumes. Returns: SMA, EMA, RSI, MACD, Bollinger Bands, Stochastic %K, ATR, ROC, composite signals (overbought/oversold), and trend classification.
risk_correlation
N x N correlation and covariance matrices from return series. Use when computing an N×N correlation matrix for multiple assets. Provide a 2D array of return series. Returns: Pearson correlation matrix, covariance matrix, and eigenvalues for PCA analysis.
risk_position-size
Fixed fractional position sizing with risk/reward targets. Use when calculating how many shares/contracts to buy given account size and risk tolerance. Provide account value, risk percentage, entry price, and stop-loss price. Returns: position size, dollar risk, and shares to trade.
risk_drawdown
Drawdown decomposition with underwater curve. Use when analyzing drawdown characteristics of a return series. Provide an array of returns. Returns: max drawdown, drawdown duration, recovery time, current drawdown, and all drawdown periods with start/end indices.
indicators_regime
Trend + volatility regime + composite risk classification. Use when classifying market regime (trending vs ranging, high vs low volatility). Provide a price series. Returns: trend regime (bullish/bearish/neutral), volatility regime (high/low/normal), and regime change signals.
indicators_crossover
Golden/death cross detection with signal history. Use when detecting moving average crossovers (golden cross, death cross). Provide prices and two MA periods. Returns: current MA values, crossover signals, crossover history, and signal strength.
fixed-income_bond
Bond price, Macaulay/modified duration, convexity, DV01. Use when pricing a bond or computing yield, duration, and convexity. Provide face value, coupon rate, maturity, and yield or price. Returns: bond price (or yield), Macaulay duration, modified duration, convexity, and accrued interest.
fixed-income_amortization
Full amortization schedule with extra payment savings analysis. Use when generating a loan amortization schedule. Provide principal, annual rate, and term in months. Returns: monthly payment, total interest, and a period-by-period schedule of principal, interest, and remaining balance.
portfolio_optimize
Portfolio optimization: max Sharpe, min vol, or risk parity weights. Use when optimizing portfolio weights for max Sharpe, min volatility, or risk parity. Provide expected returns and a covariance matrix. Returns: optimal weights, expected return, volatility, Sharpe ratio, and efficient frontier points.
derivatives_binomial-tree
CRR binomial tree pricing for American and European options. Use when pricing American or European options via the CRR binomial lattice. Provide spot, strike, time, rate, volatility, steps, and exercise style. Returns: option price, early exercise boundary, and tree node values.
derivatives_barrier-option
Barrier option pricing using analytical formulas. Use when pricing knock-in or knock-out barrier options. Provide spot, strike, barrier level, barrier type, and standard option parameters. Returns: barrier option price, vanilla equivalent, and barrier adjustment factors.
derivatives_asian-option
Asian option pricing: geometric closed-form or arithmetic approximation. Use when pricing Asian (average-price) options. Provide spot, strike, time, rate, volatility, and averaging type. Returns: option price via geometric closed-form or Turnbull-Wakeman approximation.
derivatives_lookback-option
Lookback option pricing (floating/fixed strike). Use when pricing lookback options (floating or fixed strike). Provide spot, strike, min/max price, time, rate, and volatility. Returns: lookback option price via Goldman-Sosin-Gatto formulas.
derivatives_option-chain-analysis
Option chain analytics: skew, max pain, put-call ratios. Use when analyzing an options chain for skew, max pain, and put-call ratios. Provide arrays of strikes, calls, puts, and open interest. Returns: max pain strike, put-call ratio, skew metrics, and implied volatility smile data.
derivatives_put-call-parity
Put-call parity check and arbitrage detection. Use when checking put-call parity or detecting arbitrage opportunities. Provide call price, put price, spot, strike, rate, and time. Returns: parity check, theoretical values, and any arbitrage amount.
derivatives_volatility-surface
Build implied volatility surface from market data. Use when constructing an implied volatility surface from market data. Provide arrays of strikes, expiries, and IV values. Returns: interpolated IV surface, skew metrics, term structure, and smile parameters.
stats_linear-regression
OLS linear regression with R-squared, t-stats, and standard errors. Use when fitting a linear regression (OLS). Provide x and y arrays. Returns: slope, intercept, R², adjusted R², t-statistics, p-values, standard errors, confidence intervals, and residuals.
stats_polynomial-regression
Polynomial regression of degree n with goodness-of-fit metrics. Use when fitting a polynomial of degree n to data. Provide x, y arrays, and degree. Returns: coefficients, R², fitted values, and residuals.
stats_cointegration
Engle-Granger cointegration test with hedge ratio and half-life. Use when testing if two time series are cointegrated (mean-reverting pair). Provide two price series. Returns: Engle-Granger test statistic, p-value, critical values, hedge ratio, and spread series.
stats_hurst-exponent
Hurst exponent via rescaled range (R/S) analysis. Use when determining if a time series is mean-reverting (H<0.5), random walk (H=0.5), or trending (H>0.5). Provide a price or return series. Returns: Hurst exponent via R/S analysis, classification, and confidence.
stats_garch-forecast
GARCH(1,1) volatility forecast using maximum likelihood estimation. Use when forecasting future volatility using a GARCH(1,1) model. Provide a return series. Returns: GARCH parameters (omega, alpha, beta), current conditional volatility, and multi-step ahead volatility forecasts.
stats_zscore
Rolling and static z-scores with extreme value detection. Use when computing z-scores for statistical analysis or detecting extremes. Provide a value or array and reference statistics. Returns: z-scores, mean, standard deviation, and flags for values beyond 2σ or 3σ.
stats_distribution-fit
Fit data to common distributions and rank by goodness of fit. Use when fitting data to standard distributions (normal, lognormal, uniform). Provide a data array. Returns: best-fit distribution, parameters (mean, std, etc.), goodness-of-fit statistics (KS test, chi-squared), and Q-Q plot data.
stats_correlation-matrix
Correlation and covariance matrices with optional eigenvalue decomposition. Use when computing a correlation matrix with eigenvalue decomposition for multiple assets. Provide a 2D array of return series. Returns: Pearson and Spearman correlation matrices, eigenvalues, eigenvectors, and explained variance ratios.
crypto_impermanent-loss
Impermanent loss calculator for Uniswap v2/v3 AMM positions. Use when calculating impermanent loss for a liquidity provider position. Provide initial prices and current prices for two tokens. Returns: impermanent loss percentage, hold value vs LP value, and breakeven price ratios.
crypto_apy-apr-convert
Convert between APY and APR with configurable compounding frequency. Use when converting between APY and APR with different compounding frequencies. Provide rate and compounding periods. Returns: equivalent APY, APR, daily/weekly/monthly rates, and effective annual rate.
crypto_liquidation-price
Liquidation price calculator for leveraged positions. Perp positions: funding erodes collateral over time — pull the live rate from /v1/live/funding-rates. Use when computing the liquidation price for a leveraged position. Provide entry price, leverage, position side, and maintenance margin. Returns: liquidation price, distance to liquidation, and margin call price.
crypto_funding-rate
Funding rate analysis with annualization and regime detection. Use when analyzing perpetual futures funding rates. Provide funding rate, position size, and holding period. Returns: annualized funding cost, projected payments, and carry trade opportunity estimate.
crypto_dex-slippage
DEX slippage estimator for constant-product AMM (x*y=k). Use when estimating slippage on a DEX trade using constant-product AMM math. Provide trade size and pool reserves. Returns: effective price, price impact percentage, and output amount after slippage.
crypto_vesting-schedule
Token vesting schedule with cliff, linear/graded unlock, and TGE. Use when computing a token vesting schedule with cliff and linear vesting. Provide total tokens, cliff period, vesting duration, and TGE unlock percentage. Returns: period-by-period unlock schedule with cumulative totals.
crypto_rebalance-threshold
Portfolio rebalance analyzer: drift detection and trade computation. Use when checking if a crypto portfolio needs rebalancing. Provide target weights and current weights. Returns: whether rebalancing is needed, drift per asset, and trade list to restore targets.
fx_interest-rate-parity
Interest rate parity calculator with arbitrage detection. Use when computing covered/uncovered interest rate parity for FX pairs. Provide domestic rate, foreign rate, and spot rate. Returns: theoretical forward rate, parity-implied rate, and arbitrage opportunity if any.
fx_purchasing-power-parity
Purchasing power parity fair value estimation. Use when estimating fair value of an FX rate using PPP. Provide domestic and foreign price indices and base-period exchange rate. Returns: PPP-implied fair value rate and over/undervaluation percentage.
fx_forward-rate
Bootstrap forward rates from a spot yield curve. Use when bootstrapping forward rates from a yield curve. Provide spot rates at various tenors. Returns: implied forward rates between each tenor pair.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"quantoracle": {
"quantoracle": {
"command": "npx",
"args": [
"-y",
"quantoracle-mcp"
]
}
}
}
}McpServers
{
"quantoracle": {
"command": "npx",
"args": [
"-y",
"quantoracle-mcp"
]
}
}"status_url":"https://api.quantoracle.dev/v1/watch/w_...", ...}
No exchange keys, no custody, no execution — Watch reads public market data and sends webhooks, so the worst failure mode is a missed alert (the watcher heartbeat is published in /health as watcher_heartbeat_age_s). Webhook targets are SSRF-guarded and deliveries retried. The economics: a DIY loop polling the same math once a minute past the free tier costs ~$7.20/day in per-call fees vs $5 per 30 days. Full walkthrough: quantoracle.dev/writing/crypto-liquidation-alerts-for-agents.
x402 Payments
QuantOracle uses the x402 protocol for pay-per-call micropayments. When an agent exhausts its free tier (or calls a paid-only composite), the API returns a standard 402 response with payment instructions advertising both Base and Solana. x402-compatible agents (Coinbase AgentKit, AgentCash, OpenClaw, etc.) handle the rest automatically:
1. Agent calls endpoint, gets 402 with PAYMENT-REQUIRED header listing accepted networks
2. Agent signs a gasless USDC transfer authorization on Base (EIP-3009) or Solana
3. Agent resends request with PAYMENT-SIGNATURE header
4. Server verifies via CDP facilitator, serves the response, settles on-chain
No API keys. No subscriptions. No accounts. Just math and micropayments.
Supported Networks
| Network | Asset | Gas | Best for |
|---------|-------|-----|----------|
| Base mainnet (eip155:8453) | USDC (0x8335...) | ~$0.005/tx | EVM agents, Coinbase tooling, LangChain, Base ecosystem |
| Solana mainnet (solana:5eykt4...) | USDC (EPjFWdd5...) | ~$0.0002/tx (CDP fee-payer) | Solana Agent Kit, Eliza, high-frequency bots |
- Settlement: Via Coinbase Developer Platform facilitator (api.cdp.coinbase.com/platform/v2/x402)
- Base wallet: 0xC94f5F33ae446a50Ce31157db81253BfddFE2af6
- Solana wallet: 9biztrXscReJ3Wi8EfkD2gL3WXzYUmzTEohD26Bxp39u
- Discovery: https://api.quantoracle.dev/.well-known/x402 (returns both chains for every endpoint)
Test it with AgentCash
npx agentcash@latest onboard
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