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Riskmodels MCP Server

@BlueWaterCorp

基本信息

分类

金融与商务

传输方式

stdio

作者

BlueWaterCorp

提交者

Conrad Gann

关于 Riskmodels MCP Server

US equity factor risk decomposition, ETF hedge ratios and fundamentals over MCP.

Riskmodels MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "riskmodels": {
      "command": "npx",
      "args": [
        "-y",
        "@riskmodels/mcp"
      ],
      "env": {
        "RISKMODELS_API_KEY": "<your key from riskmodels.app/get-key>"
      }
    }
  }
}

Riskmodels MCP Server 工具

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当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is RiskModels?

RiskModels provides clean dividend-adjusted total returns, factor risk decomposition, return attribution, and ETF-executable hedge ratios for US equities. It is delivered over REST, a typed Python SDK, and a built-in MCP (Model Context Protocol) server. The dataset covers ~16,000 US stocks historically, with a monthly headline universe of the largest ~3,000 by market cap.

How to use RiskModels?

Install the Python SDK with pip install riskmodels-py, then create a RiskModelsClient and call methods like client.analyze(). For AI agent integration, connect to the hosted MCP server via SSE at https://riskmodels.app/api/mcp/sse or run the local MCP server with stdio transport for tools like riskmodels_decompose and riskmodels_hedge_position. A CLI tool is also available via npm.

Key features of RiskModels

  • Daily factor decompositions for market, sector, and subsector
  • Dollar-denominated ETF hedge ratios (L1/L2/L3) for liquid ETFs
  • Historical split- and dividend-adjusted returns from 2006-01-04
  • Built-in MCP server for AI agent and LLM integration
  • Python SDK with agent-native helpers and LLM-ready context formatting
  • OAuth2 authentication and per-request billing

Use cases of RiskModels

  • Decompose portfolio risk into market, sector, and subsector components
  • Obtain executable hedge ratios for individual US equity positions
  • Perform return attribution for a universe of ~3,000 US stocks
  • Integrate factor risk analysis directly into AI agent workflows via MCP

常见问题

1

What data coverage does RiskModels offer?

The historical panel covers ~16,000 US stocks. The monthly headline universe for daily outputs is the largest ~3,000 stocks by market cap. Split- and dividend-adjusted returns begin on 2006-01-04. Served hedge ratios begin on 2010-12-08, shares and stock variance on 2011-12-07, and L* residual outputs on 2013-01-01.

2

How do I connect an AI agent to RiskModels?

Use the hosted MCP server’s SSE endpoint at `https://riskmodels.app/api/mcp/sse` with a Bearer token (API key or OAuth2 JWT). Alternatively, run the local MCP server from this repository for stdio transport, which exposes tools like `riskmodels_decompose` and `riskmodels_hedge_position`.

3

What authentication options are available?

The API supports OAuth2 and bearer token authentication using an API key. API keys can be obtained from the developer portal at `riskmodels.app/get-key`.

4

Are the hedge ratios designed for actual trading?

Yes. The published L1/L2/L3 hedge ratios are dollar-denominated and designed to remain executable with liquid raw ETFs, not with synthetic or orthogonalized factors.

5

What are the historical data start dates?

Adjusted return series begin on 2006-01-04. Served hedge ratios begin on 2010-12-08, shares and stock variance on 2011-12-07, and L* residual outputs on 2013-01-01. Data is updated daily.

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