# hpsilab-quant-finance-mcp

> hpsilab-quant-finance-mcp — haiyunsky-hpsilab-quant-finance-mcp. Use this tool when you need to analyze stocks, options, and volatility, or simulate financial scenarios using Monte Carlo methods and AI predictions. It provides a quant finance MCP server for backtesting and evaluating investment strategies, accepting financial data as input and outputting analytical results and predictions. Ideal for use cases requiring advanced financial modeling and simulation, such as portfolio optimization and risk management.

Canonical page: https://skillsregistry.net/skills/haiyunsky-hpsilab-quant-finance-mcp  
JSON: https://api.skillsregistry.net/v1/skills/haiyunsky-hpsilab-quant-finance-mcp

## Description

Quant finance MCP server for stock analysis, options analytics, implied volatility, Monte Carlo simulation, AI prediction, and backtesting.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/haiyunsky/hpsilab-quant-finance-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "haiyunsky-hpsilab-quant-finance-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/haiyunsky-hpsilab-quant-finance-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/haiyunsky-hpsilab-quant-finance-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt