QuantRisk
MCP serverDatabases & dataGive your AI portfolio risk analytics. Once added, your AI can measure portfolio risk, model future returns, stress test against market crises, and calculate option Greeks. It can also help find optimal allocations and break down performance.
Use QuantRisk in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add QuantRisk and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use QuantRisk to analyze risk
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Details
Available today. Use it from your connected AI after setup. It ran on Ahel's own infrastructure and offers 10 tools.
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Add it, then ask your AI to analyze a portfolio's risk or run a Monte Carlo simulation on your holdings.
What your AI can do with it
- Measure portfolio risk with Value at Risk, volatility, beta, and max drawdown
- Model future returns with Monte Carlo simulations showing percentile outcomes
- Stress test portfolios against crisis scenarios like the 2008 financial crisis or COVID 2020
- Find optimal portfolio allocations, such as the mix that minimizes variance or maximizes risk-adjusted returns
- Calculate option Greeks like delta, gamma, theta, vega, and rho
- Compare two or more portfolio allocations head-to-head across risk and return metrics
Install QuantRisk
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user quantrisk 'https://quantrisk-mcp.quantrisk.workers.dev/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://quantrisk-mcp.quantrisk.workers.dev/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=quantrisk&config=eyJ1cmwiOiJodHRwczovL3F1YW50cmlzay1tY3AucXVhbnRyaXNrLndvcmtlcnMuZGV2L21jcCJ9Open the link and Cursor adds the server at that address.
ChatGPT
https://quantrisk-mcp.quantrisk.workers.dev/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add quantrisk --url 'https://quantrisk-mcp.quantrisk.workers.dev/mcp'Run it once, then sign in with codex mcp login quantrisk if the server asks for an account.
From the project's README
As published by 78degrees/mcp-server in README.md.
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-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
Tools it gives your AI (10)
| Tool | What it does |
|---|---|
| analyze_risk | Calculate core risk metrics for a portfolio — Value at Risk (VaR), Conditional VaR (CVaR), volatility, beta, and max drawdown. |
| monte_carlo_simulation | Run Monte Carlo simulation on a portfolio to model the distribution of future returns, including percentile outcomes and probability of loss. |
| stress_test | Stress test a portfolio against historical crisis scenarios (GFC 2008, COVID 2020, etc.) or custom shocks (paid tier). |
| optimize_portfolio | Find the optimal portfolio allocation using mean-variance optimization. Supports max Sharpe, min variance, and target return objectives. Paid tier only. |
| correlation_matrix | Compute the pairwise correlation matrix for a set of assets. Identifies highly correlated pairs and diversification opportunities. |
| performance_attribution | Break down portfolio performance into factor exposures, sector allocation, and position contributions. Computes Sharpe, Sortino, Treynor, Calmar, and Information ratios. |
| sector_exposure | Break down portfolio exposure by GICS sector, market cap, and asset class. Returns concentration metrics including the Herfindahl-Hirschman Index. |
| price_history | Fetch historical OHLCV price data for one or more tickers. Free tier: 1 ticker, 252 days. Paid tier: up to 20 tickers, 1260 days. |
| compare_portfolios | Compare two or more portfolio allocations head-to-head across all key risk and return metrics. Paid tier only. |
| calculate_greeks | 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. |
Signals
- GitHub stars
- 2
- Forks
- 1
- Last commit
- May 2026
- Tools captured
- 10
Advanced
- Delivery
- QuantRisk MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
dev-quantrisk-mcp-server- Source
- github.com/78degrees/mcp-server
- Hosted endpoint
https://quantrisk-mcp.quantrisk.workers.dev/mcp
github.com/78degrees/mcp-server
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