QuantRisk-MCP-Server
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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.
Website · Get Pro · Documentation
Quick Start
1. Install
npm install -g @quantrisk/mcp-server2. 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.
Related MCP server: optionslab
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 |
| VaR, CVaR, volatility, Sharpe ratio, max drawdown | Free |
| Forward-looking return simulations with configurable paths | Free |
| Portfolio impact under historical and hypothetical scenarios | Free |
| Historical price and return data for any supported ticker | Free |
| Sector and industry breakdown across holdings | Free |
| Return attribution by asset, sector, and factor | Free |
| Cross-asset correlation analysis | Free |
| Mean-variance and risk-parity optimization | Pro |
| Side-by-side risk/return comparison of multiple portfolios | Pro |
| 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 testSee CONTRIBUTING.md for guidelines.
License
Built by the team at quantrisk.dev
Contact: hello@quantrisk.dev
Available Tools
10 toolsanalyze_riskBInspect
Calculate core risk metrics for a portfolio — Value at Risk (VaR), Conditional VaR (CVaR), volatility, beta, and max drawdown.
Inputs: positions (required), confidence_level, horizon_days, method, +2 more.
calculate_greeksAInspect
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.
Inputs: options (required), risk_free_rate.
compare_portfoliosBInspect
Compare two or more portfolio allocations head-to-head across all key risk and return metrics. Paid tier only.
Inputs: portfolios (required), period_days, confidence_level.
correlation_matrixAInspect
Compute the pairwise correlation matrix for a set of assets. Identifies highly correlated pairs and diversification opportunities.
Inputs: tickers (required), lookback_days, method.
monte_carlo_simulationAInspect
Run Monte Carlo simulation on a portfolio to model the distribution of future returns, including percentile outcomes and probability of loss.
Inputs: positions (required), num_paths, horizon_days, model, +2 more.
optimize_portfolioAInspect
Find the optimal portfolio allocation using mean-variance optimization. Supports max Sharpe, min variance, and target return objectives. Paid tier only.
Inputs: tickers (required), objective, target_return, constraints, +2 more.
performance_attributionBInspect
Break down portfolio performance into factor exposures, sector allocation, and position contributions. Computes Sharpe, Sortino, Treynor, Calmar, and Information ratios.
Inputs: positions (required), period_days, benchmark, risk_free_rate.
price_historyAInspect
Fetch historical OHLCV price data for one or more tickers. Free tier: 1 ticker, 252 days. Paid tier: up to 20 tickers, 1260 days.
Inputs: tickers (required), days, interval.
sector_exposureAInspect
Break down portfolio exposure by GICS sector, market cap, and asset class. Returns concentration metrics including the Herfindahl-Hirschman Index.
Inputs: positions (required).
stress_testBInspect
Stress test a portfolio against historical crisis scenarios (GFC 2008, COVID 2020, etc.) or custom shocks (paid tier).
Inputs: positions (required), scenarios, custom_shocks.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 10 tools
Each tool targets a distinct financial analysis function (risk metrics, greeks, comparison, correlation, simulation, optimization, attribution, history, sector exposure, stress test) with no overlap.
All tool names consistently follow the verb_noun pattern with snake_case (e.g., analyze_risk, calculate_greeks, compare_portfolios).
10 tools is well within the ideal 3-15 range, covering a comprehensive set of risk analysis capabilities without being excessive.
The tool set covers all major areas of quantitative risk analysis: basic risk metrics, options greeks, portfolio optimization, simulation, stress testing, performance attribution, correlation, sector exposure, and historical data.
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