HowRisky
by howrisky
HowRisky: Financial risk analysis with Monte Carlo simulations and fat-tail modeling for portfolios, startup valuation,
★ 1
GitHub stars
What it does
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.
About
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.
How to install
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.
License
NOASSERTION
HowRisky is released under the NOASSERTION license.
Readme
Frequently Asked Questions
- What is the HowRisky MCP server?
- HowRisky is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for HowRisky?
- This profile displays 58 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Discussion
Comments — not star reviews- No comments yet — start the thread.
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Ratings
4.5★★★★★58 reviews- ★★★★★Ganesh Mohane· Dec 28, 2024
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Amina Zhang· Dec 28, 2024
Useful MCP listing: HowRisky is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Isabella Bansal· Dec 16, 2024
HowRisky reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Isabella Agarwal· Dec 12, 2024
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Lucas Zhang· Dec 12, 2024
I recommend HowRisky for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Michael Srinivasan· Dec 8, 2024
According to our notes, HowRisky benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Yash Thakker· Nov 27, 2024
HowRisky has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Sakshi Patil· Nov 19, 2024
Useful MCP listing: HowRisky is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Lucas Liu· Nov 19, 2024
HowRisky is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Amina Liu· Nov 15, 2024
According to our notes, HowRisky benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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