# Cabrini Market Data

> Cabrini Market Data — ai-cabrini-market-data. Use this tool when you need to analyze and process large amounts of US stock market data for informed decision-making. It provides 23 years of minute bars, SEC filings, and fundamentals, solving problems related to market trend analysis, risk assessment, and investment strategy development. With historical data as input, it outputs actionable insights for AI agents to make data-driven predictions and optimize trading strategies.

Canonical page: https://skillsregistry.net/skills/ai-cabrini-market-data  
JSON: https://api.skillsregistry.net/v1/skills/ai-cabrini-market-data

## Description

US stock market data for AI agents — 23 years of minute bars, SEC filings, fundamentals.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.cabrini%2Fmarket-data)
- **Repository:** <https://github.com/nlapi/cabrini-py>

## Use it

MCP endpoint published by the skill: `https://cabrini.ai/mcp`

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": "ai-cabrini-market-data"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-cabrini-market-data` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-cabrini-market-data/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