by howrisky
HowRisky: Financial risk analysis with Monte Carlo simulations and fat-tail modeling for portfolios, startup valuation,
★ 1
GitHub stars
Provides Monte Carlo risk analysis and financial modeling with fat-tail distributions for portfolio analysis, startup valuations, and investment strategies. Uses institutional-grade algorithms to calculate risk metrics like CVaR and ruin probability.
HowRisky is a community-built MCP server published by howrisky that provides AI assistants with tools and capabilities via the Model Context Protocol. HowRisky: Financial risk analysis with Monte Carlo simulations and fat-tail modeling for portfolios, startup valuation, It is categorized under finance, analytics data.
You can install HowRisky in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
NOASSERTION
HowRisky is released under the NOASSERTION license.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Useful MCP listing: HowRisky is the kind of server we cite when onboarding engineers to host + tool permissions.
HowRisky reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend HowRisky for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, HowRisky benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
HowRisky has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: HowRisky is the kind of server we cite when onboarding engineers to host + tool permissions.
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, HowRisky benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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Monte Carlo risk analysis for AI agents. Institutional-grade financial modeling with fat-tail distributions and proprietary KDE algorithms.
8 Tools: Portfolio risk (CVaR, ruin probability), startup equity, real estate, Kelly criterion betting, and more.
Compatible with: Claude Desktop, ChatGPT Desktop, Cursor, Windsurf, Cline, GitHub Copilot, VS Code, Codex
{
"mcpServers": {
"howrisky": {
"command": "npx",
"args": ["-y", "howrisky-mcp-server"],
"env": {
"HOWRISKY_API_KEY": "your-api-key-here"
}
}
}
}
Get your free API key at: https://howrisky.ai/app/settings (100 calls/month free)
Step 1: Get your API key from https://howrisky.ai/app/settings
Step 2: Add the standard config above to your AI tool's MCP configuration
That's it! Your AI can now access Monte Carlo risk simulations.
Edit config file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonAdd the standard config above.
Restart Claude Desktop.
Test it: Ask Claude "Using HowRisky, what's the risk of a 60/40 portfolio?"
</details> <details> <summary>ChatGPT Desktop</summary>Restart ChatGPT Desktop.
Test it: Ask ChatGPT "Use HowRisky to calculate CVaR for 100% SPY portfolio"
</details> <details> <summary>Cursor</summary>Add to Cursor's MCP configuration file:
Use the standard config above.
Cursor supports MCP via VS Code extension compatibility.
</details> <details> <summary>Windsurf</summary>Add to Windsurf MCP settings:
Use the standard config above.
Windsurf's MCP integration works similarly to Cursor.
</details> <details> <summary>Cline (VS Code)</summary>Via Cline MCP Marketplace:
Manual Setup:
Add to VS Code Settings → Extensions → Cline → MCP Servers:
Use the standard config above.
</details> <details> <summary>GitHub Copilot / VS Code</summary>Add to VS Code settings.json:
Use the standard config above in the MCP servers configuration section.
</details> <details> <summary>Remote Server (HTTP)</summary>For custom integrations or web-based AI tools:
Endpoint: https://mcp.howrisky.ai
Authentication: Include X-API-Key header with your API key
Documentation: https://howrisky.ai/mcp/docs
Example:
curl -X POST https://mcp.howrisky.ai \
-H "X-API-Key: your-api-key" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","method":"tools/list","id":1}'
| Tool | Description |
|---|---|
calculate_portfolio_risk | CVaR, VaR, ruin probability, survival probability |
simulate_future_timelines | Year-by-year portfolio evolution with percentiles |
compare_portfolios | Side-by-side risk comparison of multiple portfolios |
text_to_portfolio | Natural language → asset allocations |
add_startup | Startup equity modeling with exit scenarios |
add_real_estate | Real estate with cash flows, IRR, mortgage analysis |
add_private_asset | Illiquid asset modeling (PE funds, etc.) |
add_gamble | Kelly criterion for high-risk betting strategies |
Full documentation: https://howrisky.ai/mcp/docs
Once configured, ask your AI:
"Using HowRisky, calculate the risk of investing $100K in a 60/40 portfolio over 20 years"
The AI will:
tools/listcalculate_portfolio_risk with correct parametersFat-Tail Modeling - Gaussian models underestimate crash risk by 3-10x. Our proprietary KDE captures reality.
Comprehensive Metrics - 12 risk metrics including CVaR 95/99, VaR, ruin probability, percentiles
Private Assets - Model startups, real estate, PE funds, and high-risk gambles
Tax-Aware - 15+ countries supported (US, GB, DE, FR, IT, ES, JP, AU, CA, etc.)
Custom Scenarios - Override historical data with your own market assumptions
| Tier | Calls/Month | Price |
|---|---|---|
| Free | 100 | $0 |
| Developer | 10,000 | $99 |
| Professional | 100,000 | $299 |
| Enterprise | 1,000,000 | $999 |
View pricing: https://howrisky.ai/mcp/pricing
Proprietary - Copyright © 2025 Diogo Seca / HowRisky.ai
You may use this software to access HowRisky MCP API. Modification and redistribution prohibited. See LICENSE for details.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.