
Riskmodels
@BlueWaterCorp
About Riskmodels
RiskModels provides institutional-grade equity risk decomposition via MCP. Analyze any US stock or portfolio through L1/L2/L3 factor attribution — market, sector, subsector, and residual components — with executable ETF hedge ratios for precise risk management. Built for portfoli
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"riskmodels": {
"command": "npx",
"args": [
"-y",
"@smithery/cli@latest",
"run",
"service-c09f/riskmodels"
],
"env": {
"SMITHERY_API_KEY": "<your-smithery-api-key>"
}
}
}
}Tools
No tools detected
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Overview
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
FAQ from RiskModels
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 are available from 2006-01-04; factor outputs (hedge ratios and explained risk) begin in 2007.
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.
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.
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.
What are the historical data start dates?
Adjusted return series begin on 2006-01-04. Factor outputs (hedge ratios and explained risk) are available from 2007 through present. Daily updates are applied.
Frequently asked questions
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 are available from 2006-01-04; factor outputs (hedge ratios and explained risk) begin in 2007.
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`.
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`.
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.
What are the historical data start dates?
Adjusted return series begin on 2006-01-04. Factor outputs (hedge ratios and explained risk) are available from 2007 through present. Daily updates are applied.
Basic information
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