# HPSILab - Quant Finance MCP Server for Stock Analysis and Options Analytics

> Use this tool when you need to integrate institutional-grade quantitative stock analysis and research signals into your AI system. It provides a Model Context Protocol (MCP) interface for seamless interaction, solving problems related to informed investment decisions and portfolio optimization. Ideal for use cases requiring high-quality, data-driven insights, it accepts relevant market data as input and outputs actionable research signals.

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

## Description

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tvnldd43dx)
- **Repository:** <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-mcp-server"
    }
  }
}
```

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