Summary
Plugs institutional risk analytics directly into Claude via the Model Context Protocol. Exposes 10 tools including VaR calculation, Monte Carlo simulation with configurable paths, historical stress testing, portfolio optimization, and options Greeks. Free tier gets you 7 tools and 20 positions per portfolio. Pro unlocks mean-variance optimization, 500-position portfolios, and 100k simulation paths. Runs as a local stdio process that talks to a Cloudflare Workers backend, which pulls real market data from Yahoo Finance and runs the math server-side. Useful when you need actual calculated risk metrics instead of LLM estimates, or when you're building portfolio analysis workflows that need to ground decisions in real numbers.
Install to Claude Code
verifiedclaude mcp add --transport http mcp-server https://quantrisk-mcp.quantrisk.workers.dev/mcpRun in your terminal. Add --scope user to make it available in every project.
Review the command, arguments, and environment values before installing — MCP servers run with your local permissions.
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Tools
Verified live against the running server on Jun 10, 2026.
verified live10 tools
analyze_riskCalculate core risk metrics for a portfolio — Value at Risk (VaR), Conditional VaR (CVaR), volatility, beta, and max drawdown.6 params
Calculate core risk metrics for a portfolio — Value at Risk (VaR), Conditional VaR (CVaR), volatility, beta, and max drawdown.
Parameters* required
methodstringVaR calculation method. "historical" uses empirical return distribution, "parametric" assumes normality, "cornish_fisher" adjusts for skew and kurtosis. Default: "historical".one of
historical · parametric · cornish_fisherdefault: historicalbenchmarkstringBenchmark ticker for beta calculation, e.g. SPY or QQQ. Default: SPY.default: SPY
positions*arrayArray of portfolio positions. Each entry needs a ticker and quantity. Free tier: max 20 positions. Paid tier: up to 500.
horizon_daysintegerRisk horizon in trading days. 1 = overnight, 21 ≈ 1 month, 252 ≈ 1 year. Default: 1.default: 1
lookback_daysintegerNumber of historical trading days to use. 252 ≈ 1 year, 756 ≈ 3 years. Range: 30-1260. Default: 252.default: 252
confidence_levelnumberVaR confidence level as a decimal, e.g. 0.95 = 95%. Range: 0.01-0.99. Default: 0.95.default: 0.95
monte_carlo_simulationRun Monte Carlo simulation on a portfolio to model the distribution of future returns, including percentile outcomes and probability of loss.6 params
Run Monte Carlo simulation on a portfolio to model the distribution of future returns, including percentile outcomes and probability of loss.
Parameters* required
seedvalueRandom seed for reproducible results. Omit for a fresh random run each time.
modelstringStochastic process model. "gbm" = Geometric Brownian Motion (standard), "jump_diffusion" = adds jump risk for fat-tail scenarios. Default: "gbm".one of
gbm · jump_diffusiondefault: gbmnum_pathsintegerNumber of simulation paths to run. More paths = more accurate but slower. Free tier: max 1,000. Paid tier: up to 100,000. Default: 10,000.default: 10000
positions*arrayArray of portfolio positions. Free tier: max 20 positions. Paid tier: up to 500.
horizon_daysintegerSimulation horizon in trading days. 21 ≈ 1 month, 63 ≈ 1 quarter, 252 ≈ 1 year. Default: 21.default: 21
lookback_daysintegerHistorical window used to estimate drift and volatility parameters. Range: 30-1260 trading days. Default: 252.default: 252
stress_testStress test a portfolio against historical crisis scenarios (GFC 2008, COVID 2020, etc.) or custom shocks (paid tier).3 params
Stress test a portfolio against historical crisis scenarios (GFC 2008, COVID 2020, etc.) or custom shocks (paid tier).
Parameters* required
positions*arrayArray of portfolio positions. Free tier: max 20 positions and historical scenarios only. Paid tier: up to 500 positions plus custom shocks.
scenariosarrayHistorical scenarios to run. Available values: gfc_2008, covid_2020, dot_com_2000, black_monday_1987, taper_tantrum_2013, rate_hike_2022, volmageddon_2018, euro_crisis_2011. Default: [gfc_2008, covid_2020].
custom_shocksvalueCustom shock definitions. PAID tier only. Each shock specifies ticker-level, sector-level, or market-wide price changes.
optimize_portfolioFind the optimal portfolio allocation using mean-variance optimization. Supports max Sharpe, min variance, and target return objectives. Paid tier only.6 params
Find the optimal portfolio allocation using mean-variance optimization. Supports max Sharpe, min variance, and target return objectives. Paid tier only.
Parameters* required
tickers*arrayUniverse of tickers to optimize across. Must be 2-50 tickers. The optimizer will determine the best weights within this set.
objectivestringOptimization objective. "max_sharpe" = maximize risk-adjusted return, "min_variance" = minimize portfolio volatility, "target_return" = hit a specific return with minimum risk. Default: "max_sharpe".one of
max_sharpe · min_variance · target_returndefault: max_sharpeconstraintsobjectOptional weight constraints. See ConstraintsInput for details.
lookback_daysintegerHistorical window for estimating return and covariance. 252 = 1 year, 756 = 3 years, 1260 = 5 years. Range: 252-1260. Default: 756.default: 756
target_returnvalueRequired when objective is "target_return". Annualized return as a decimal, e.g. 0.12 = 12% annual return target.
risk_free_ratenumberAnnualized risk-free rate as a decimal, e.g. 0.05 = 5%. Used in Sharpe ratio calculation. Default: 0.05.default: 0.05
correlation_matrixCompute the pairwise correlation matrix for a set of assets. Identifies highly correlated pairs and diversification opportunities.3 params
Compute the pairwise correlation matrix for a set of assets. Identifies highly correlated pairs and diversification opportunities.
Parameters* required
methodstringCorrelation method. "pearson" = linear correlation (standard), "spearman" = rank-based (robust to outliers), "kendall" = concordance-based. Default: "pearson".one of
pearson · spearman · kendalldefault: pearsontickers*arrayTickers to include in the correlation matrix. Minimum 2, maximum 50. Free tier: max 10 tickers. Paid tier: up to 50.
lookback_daysintegerHistorical window for computing correlations in trading days. 30 = ~6 weeks, 252 = ~1 year. Range: 30-1260. Default: 252.default: 252
performance_attributionBreak down portfolio performance into factor exposures, sector allocation, and position contributions. Computes Sharpe, Sortino, Treynor, Calmar, and Information ratios.4 params
Break down portfolio performance into factor exposures, sector allocation, and position contributions. Computes Sharpe, Sortino, Treynor, Calmar, and Information ratios.
Parameters* required
benchmarkstringBenchmark ticker for relative performance metrics (Information Ratio, Tracking Error, Beta). Default: SPY.default: SPY
positions*arrayArray of portfolio positions. Free tier: max 20 positions (basic ratios only). Paid tier: up to 500 positions with full factor attribution.
period_daysintegerMeasurement period in trading days. 252 = ~1 year. Range: 30-1260. Default: 252.default: 252
risk_free_ratenumberAnnualized risk-free rate as a decimal, e.g. 0.05 = 5%. Used in Sharpe, Sortino, and Treynor ratios. Default: 0.05.default: 0.05
sector_exposureBreak down portfolio exposure by GICS sector, market cap, and asset class. Returns concentration metrics including the Herfindahl-Hirschman Index.1 params
Break down portfolio exposure by GICS sector, market cap, and asset class. Returns concentration metrics including the Herfindahl-Hirschman Index.
Parameters* required
positions*arrayArray of portfolio positions to analyze. Returns GICS sector weights, market cap breakdown, and concentration metrics.
price_historyFetch historical OHLCV price data for one or more tickers. Free tier: 1 ticker, 252 days. Paid tier: up to 20 tickers, 1260 days.3 params
Fetch historical OHLCV price data for one or more tickers. Free tier: 1 ticker, 252 days. Paid tier: up to 20 tickers, 1260 days.
Parameters* required
daysintegerNumber of historical trading days to return. Free tier: max 252 days (~1 year). Paid tier: up to 1260 days (~5 years). Default: 252.default: 252
tickers*arrayTicker symbols to fetch price history for. Free tier: max 1 ticker. Paid tier: up to 20 tickers.
intervalstringPrice interval. "daily" returns one OHLCV row per trading day, "weekly" aggregates to weekly bars, "monthly" aggregates to monthly bars. Default: "daily".one of
daily · weekly · monthlydefault: dailycompare_portfoliosCompare two or more portfolio allocations head-to-head across all key risk and return metrics. Paid tier only.3 params
Compare two or more portfolio allocations head-to-head across all key risk and return metrics. Paid tier only.
Parameters* required
portfolios*arrayTwo to five named portfolios to compare head-to-head. Each needs a unique name and a list of positions. Min: 2, max: 5.
period_daysintegerLookback period in trading days used for return and risk calculations. 252 = ~1 year. Range: 30-1260. Default: 252.default: 252
confidence_levelnumberVaR confidence level as a decimal, e.g. 0.95 = 95%. Range: 0.01-0.99. Default: 0.95.default: 0.95
calculate_greeksCalculate option Greeks (delta, gamma, theta, vega, rho) for individual options or an options portfolio. Uses Black-Scholes for European, binomial for American style. Paid tier only.2 params
Calculate option Greeks (delta, gamma, theta, vega, rho) for individual options or an options portfolio. Uses Black-Scholes for European, binomial for American style. Paid tier only.
Parameters* required
options*arrayArray of option positions to calculate Greeks for. 1-100 options. Results include per-option Greeks and aggregated portfolio Greeks.
risk_free_ratenumberAnnualized risk-free rate as a decimal, e.g. 0.05 = 5%. Used in Black-Scholes and binomial pricing models. Default: 0.05.default: 0.05
QuantRisk
Institutional-grade portfolio risk analytics for Claude and any MCP client.
VaR / Monte Carlo / Stress Testing / Portfolio Optimization / Greeks / Correlation Matrices
Real market data. Real math. Not hallucinated numbers.
Quick Start
1. Install
npm install -g @quantrisk/mcp-server
2. Configure (Claude Desktop — see below for Cursor)
Add to your claude_desktop_config.json:
{
"mcpServers": {
"quantrisk": {
"command": "quantrisk-mcp-server",
"env": {
"QUANTRISK_API_KEY": "your-api-key"
}
}
}
}
Get your free API key at quantrisk.dev/signup.
3. Ask Claude
"What's the Value at Risk on a portfolio of 60% SPY, 25% TLT, and 15% GLD?"
That's it. Claude now has access to institutional-grade risk analytics.
Configuration
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"quantrisk": {
"command": "quantrisk-mcp-server",
"env": {
"QUANTRISK_API_KEY": "your-api-key"
}
}
}
}
Cursor
Add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"quantrisk": {
"command": "quantrisk-mcp-server",
"env": {
"QUANTRISK_API_KEY": "your-api-key"
}
}
}
}
Any MCP Client
QuantRisk works with any client that supports the Model Context Protocol. Point it at the quantrisk-mcp-server binary with your API key in the environment.
Tools
| Tool | Description | Tier |
|---|---|---|
analyze_risk | VaR, CVaR, volatility, Sharpe ratio, max drawdown | Free |
monte_carlo_simulation | Forward-looking return simulations with configurable paths | Free |
stress_test | Portfolio impact under historical and hypothetical scenarios | Free |
price_history | Historical price and return data for any supported ticker | Free |
sector_exposure | Sector and industry breakdown across holdings | Free |
performance_attribution | Return attribution by asset, sector, and factor | Free |
correlation_matrix | Cross-asset correlation analysis | Free |
optimize_portfolio | Mean-variance and risk-parity optimization | Pro |
compare_portfolios | Side-by-side risk/return comparison of multiple portfolios | Pro |
calculate_greeks | Options Greeks — delta, gamma, theta, vega, rho | Pro |
Example Queries
Once configured, ask Claude questions like these:
- "Run a Monte Carlo simulation on my portfolio: 50% AAPL, 30% MSFT, 20% NVDA. Show me the 5th percentile outcome."
- "Stress test 70% VTI / 30% BND against the 2008 financial crisis and a hypothetical 300bp rate shock."
- "What's my sector exposure if I hold equal weights in AMZN, JPM, JNJ, XOM, and NEE?"
- "Show me the correlation matrix for SPY, GLD, TLT, and BTC-USD over the last 2 years."
- "Compare the risk-adjusted returns of a 60/40 portfolio vs. an all-weather portfolio." (Pro)
- "Calculate the Greeks for a SPY 550 call expiring in 30 days." (Pro)
Why Pro?
The free tier covers core risk analytics for small portfolios. Pro unlocks the tools and scale that serious analysis demands.
| Free | Pro ($29/mo) | |
|---|---|---|
| Positions | 20 | 500 |
| API calls | 50/day | Unlimited |
| Tools | 7 | All 10 |
| Monte Carlo paths | 1,000 | 100,000 |
| Portfolio optimization | — | Mean-variance, risk-parity, min-volatility |
| Portfolio comparison | — | Side-by-side multi-portfolio analysis |
| Options Greeks | — | Full Greeks surface |
What that means in practice:
- Free: "What's the VaR on my 10-stock portfolio?" — works great.
- Pro: "Optimize my 200-position portfolio for maximum Sharpe, then stress test it against 5 scenarios and compare it to my current allocation." — you need Pro for that.
How It Works
Claude / MCP Client
|
MCP Protocol
|
QuantRisk MCP Server (local process)
|
QuantRisk API (Cloudflare Workers)
|
Yahoo Finance (market data) + risk engine (math)
- MCP Server runs locally as a stdio process — your API key never leaves your machine except to authenticate with the QuantRisk API.
- Risk Engine runs on Cloudflare Workers. All calculations — VaR, Monte Carlo, optimization — happen server-side with real math on real market data.
- Market Data sourced from Yahoo Finance. Prices, fundamentals, and options chains are fetched in real time.
- Reports generated with pdf-lib when applicable.
No data is stored. No portfolio information is retained after a request completes.
Contributing
Contributions are welcome. Please open an issue first to discuss what you'd like to change.
git clone https://github.com/78degrees/mcp-server.git
cd mcp-server
npm install
npm test
See CONTRIBUTING.md for guidelines.
License
Built by the team at quantrisk.dev
Contact: hello@quantrisk.dev
Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →Configuration
QUANTRISK_API_KEYsecretAPI key from https://quantrisk.dev/upgrade. Optional — without one, requests run on the free tier (limited tools and call quotas).
Categories
Registryactive
Package@quantrisk/mcp-server
TransportSTDIO, HTTP
AuthRequired
Tools verifiedJun 10, 2026
UpdatedMay 9, 2026
