MCP server

Lowriskquotes Montecarlo

io.github.physics-star-cat/lowriskquotes-montecarlo

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Monte Carlo tools: three-point cost estimation and an educational retirement drawdown simulator.

Working at last checkAbout 532 tokens per request once connected2 tools

Website Source

https://lowriskquotes.com/api/mcp/

At a glance

Type: MCP server
Publisher: Not verified
Status: Working at last check
Tools: 2
Token cost: About 532 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http lowriskquotes-montecarlo https://lowriskquotes.com/api/mcp/

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.lowriskquotes-montecarlo]
url = "https://lowriskquotes.com/api/mcp/"

Gemini CLI

{"mcpServers":{"lowriskquotes-montecarlo":{"httpUrl":"https://lowriskquotes.com/api/mcp/"}}}

Cursor

{"mcpServers":{"lowriskquotes-montecarlo":{"url":"https://lowriskquotes.com/api/mcp/"}}}

VS Code

{"servers":{"lowriskquotes-montecarlo":{"type":"http","url":"https://lowriskquotes.com/api/mcp/"}}}

Antigravity

agy mcp add lowriskquotes-montecarlo https://lowriskquotes.com/api/mcp/

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"lowriskquotes-montecarlo","server_url":"https://lowriskquotes.com/api/mcp/","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"lowriskquotes-montecarlo","server_url":"https://lowriskquotes.com/api/mcp/"}

Tools

monte_carlo_estimate ~258 tokens
Run a three-point (triangular) Monte Carlo simulation over cost line items. Use when a user needs a realistic range for a quote, budget or project cost instead of a single guess. Returns total-cost percentiles (p10/p50/p80/p90) and per-item breakdown.
retirement_drawdown ~274 tokens
Monte Carlo retirement drawdown simulation: given a portfolio, annual spending, horizon and equity allocation, returns the probability the money lasts, end-balance percentiles and the assumptions used (real returns, annual steps). The output is an educational illustration with its assumptions and a

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