RiskModels
NPM · @RISKMODELS/MCP · 2 COMPONENTS · SCANNED SEP 20
Dividend-adjusted US equity total returns, risk decomposition, attribution & ETF hedge ratios
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 32 of 97 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency32
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: no license is declared. See how to fix → Fail
- Actively maintained (last published 101 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability85
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 2925 tokens (~76/item across 38 items; 29 tools + 9 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management97
- Stability observed for 29 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage99
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 96% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 29 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 30 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the RiskModels MCP server?
RiskModels runs locally as an npm package, launched with npx -y @riskmodels/mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · @riskmodels/mcp
claude mcp add bluewatercorp-riskmodels -- npx -y @riskmodels/mcp
{
"mcpServers": {
"bluewatercorp-riskmodels": {
"command": "npx",
"args": [
"-y",
"@riskmodels/mcp"
]
}
}
} {
"servers": {
"bluewatercorp-riskmodels": {
"command": "npx",
"args": [
"-y",
"@riskmodels/mcp"
]
}
}
} codex mcp add bluewatercorp-riskmodels -- npx -y @riskmodels/mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"bluewatercorp-riskmodels": {
"type": "local",
"command": [
"npx",
"-y",
"@riskmodels/mcp"
],
"enabled": true
}
}
} openclaw mcp add bluewatercorp-riskmodels --command npx --arg -y --arg @riskmodels/mcp
mcp_servers:
bluewatercorp-riskmodels:
command: "npx"
args: ["-y", "@riskmodels/mcp"] {
"McpServers": {
"bluewatercorp-riskmodels": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"@riskmodels/mcp"
]
}
}
} assistant mcp add bluewatercorp-riskmodels -t stdio -c npx -a -y @riskmodels/mcp
{
"mcpServers": {
"bluewatercorp-riskmodels": {
"command": "npx",
"args": [
"-y",
"@riskmodels/mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 20 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 19 Sept 26 0
- Security disclosure: unverified → fail ▼ functional
- 18 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 0
- Security disclosure: fail → unverified ▼ functional
- 16 Sept 26 −2
- Stability: pass → 0.83 functional
- 15 Sept 26 0
- Stability: 0.97 → pass security
- Security disclosure: unverified → fail ▼ functional
- 14 Sept 26 +1
- Security disclosure: fail → unverified ▼ functional
- 12 Sept 26 +1
- Security disclosure: unverified → fail ▼ functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed npm/@riskmodels/mcp@1.0.6
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 97 packages
| Packages resolved | 97 |
|---|---|
| Stale | 31 |
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
get_l3_decomposition L3 Hierarchical Risk Decomposition ~126
Daily EOD hierarchical orthogonal decomposition for a single ticker: market → sector → subsector → residual. Returns parallel time-series arrays plus hedge ratios. Historical data from GCP zarr; latest snapshot from Supabase. Data freshness: daily after US market close (see _data_as_of).
| Name | Type | Req | Description |
|---|---|---|---|
| market_factor_etf | string | – | Market factor ETF for L1 (default SPY) |
| ticker | string | yes | Stock ticker symbol, e.g. NVDA, AAPL |
| years | integer | – | Years of daily history to return (1–15) |
No output schema declared.
No examples provided.
get_metrics Latest Risk Metrics Snapshot ~89
Latest daily EOD risk metrics for a ticker from the Supabase _latest table: L1/L2/L3 hedge ratios (SPY, sector ETF, subsector ETF), explained-risk fractions, daily volatility, price close, market cap. Single-row snapshot. Data freshness: daily after US market close.
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | Stock ticker symbol, e.g. NVDA, AAPL |
No output schema declared.
No examples provided.
get_portfolio_risk_snapshot Portfolio Risk Snapshot ~153
Bundled portfolio risk report for up to 100 positions: variance decomposition (market / sector / subsector / residual / systematic), portfolio 23-day volatility, and optional diversification analytics with sector/subsector ETF correlation matrices. Returns JSON by default. Response is cached per-user per-portfolio for 1 hour.
| Name | Type | Req | Description |
|---|---|---|---|
| as_of_date | string | – | YYYY-MM-DD override for the snapshot date |
| include_diversification | boolean | – | Include diversification metrics (adds latency) |
| positions | array | yes | Positions as { ticker, weight } pairs. Weights need not sum to 1. |
| title | string | – | – |
| window_days | integer | – | Rolling window in trading days for diversification |
No output schema declared.
No examples provided.
post_snapshot Canonical Portfolio Snapshot ~199
Run a canonical risk snapshot on a portfolio (1–100 positions): L3 variance decomposition (market / sector / subsector / residual / systematic), L3 hedge ratios per position, frozen-weight daily return attribution (gross + market / sector / subsector strips + residual), cumulative return and drawdown over the lookback window, and a risk_summary with dominant drivers, concentration flags, and top exposures. This is the canonical RiskModels public surface — same response shape across UI, CLI, SDK, and agents. Provide either weight or shares for every position (do not mix). Bills as portfolio-risk-snapshot ($0.25 per request).
| Name | Type | Req | Description |
|---|---|---|---|
| benchmark | string | – | Optional benchmark ticker (reserved for comparison views) |
| lookback_days | integer | – | Trading days of history for return curves and attribution series (default 252) |
| portfolio | array | yes | Portfolio positions. Use weights for every position OR shares for every position — do not mix. |
No output schema declared.
No examples provided.
riskmodels_analyze_portfolio RiskModels Portfolio hedge_levels aggregate ~85
Holdings-weighted L1/L2/L3 hedge_levels across names via POST /batch/analyze (hedge_ratios). Returns normalized portfolio.portfolio_hedge_levels and per-ticker blocks when present.
| Name | Type | Req | Description |
|---|---|---|---|
| positions | array | yes | Positions with weight or dollars (combined per ticker) |
| years | integer | – | Batch lookback window, default 1 |
No output schema declared.
No examples provided.
riskmodels_call_endpoint RiskModels Generic Capability Call ~147
Escape hatch for any capability without a dedicated tool. Run riskmodels_list_endpoints (and riskmodels_get_capability for params), then call with that capability's method + endpoint path. Path is relative to the API root (a leading "/api" is stripped). Blocked: SQL (/cli/query), Plaid, and chat endpoints — use the REST API directly for those.
| Name | Type | Req | Description |
|---|---|---|---|
| body | object | – | JSON body (POST) |
| method | string | yes | HTTP method from list_endpoints |
| path | string | yes | Endpoint path from list_endpoints, e.g. "/industry-panel" or "/data/benchmark/SPY" |
| query | object | – | Query parameters |
No output schema declared.
No examples provided.
riskmodels_compare RiskModels Multi-Ticker Comparison ~48
Compare tickers across market, sector, subsector, and residual risk layers. Prefer grouped bar charts when chart_data is present.
| Name | Type | Req | Description |
|---|---|---|---|
| tickers | array | yes | Ticker symbols to compare |
No output schema declared.
No examples provided.
riskmodels_decompose RiskModels Single-Stock Decomposition ~111
L3 four-bet view: decompose one stock into additive market, sector, subsector, and residual layers (same semantics as POST /decompose exposure/hedge). Returns chart_data and plain_english. To compare standalone L1 vs L2 vs L3 hedge solutions (HR/ER + ETF legs), call riskmodels_get_hedge_levels or read hedge_levels on the API response.
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | Ticker symbol, e.g. NVDA or AAPL |
No output schema declared.
No examples provided.
riskmodels_get_capability Get RiskModels Capability Details ~45
Get full capability details (parameters, pricing, examples) by id
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | Capability id (e.g. ticker-returns, risk-decomposition) |
No output schema declared.
No examples provided.
riskmodels_get_etf RiskModels ETF Metrics ~61
Latest canonical metrics for one ETF (GET /data/etf/{ticker}): registry metadata + portfolio surface. Resolve the ticker via riskmodels_search_etfs if unsure.
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | ETF ticker, e.g. SMH |
No output schema declared.
No examples provided.
riskmodels_get_etf_holdings RiskModels ETF Holdings ~62
Top-N current holdings of an ETF (GET /data/etf/{ticker}/holdings).
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | ETF ticker, e.g. SMH |
| top | integer | – | Number of holdings (default 25) |
No output schema declared.
No examples provided.
riskmodels_get_filer_holdings RiskModels 13F Filer Holdings ~86
Top-N current holdings of a 13F filer (GET /13f/filers/{bw_filer_id}/holdings). Resolve bw_filer_id via riskmodels_search_filers first.
| Name | Type | Req | Description |
|---|---|---|---|
| bw_filer_id | string | yes | Filer id from riskmodels_search_filers |
| top | integer | – | Number of holdings (default 25) |
No output schema declared.
No examples provided.
riskmodels_get_filer_snapshot RiskModels 13F Filer Snapshot ~77
Composed JSON snapshot for one 13F filer (GET /13f/filers/{bw_filer_id}/snapshot): registry + latest metrics + concentration. Resolve bw_filer_id via riskmodels_search_filers first.
| Name | Type | Req | Description |
|---|---|---|---|
| bw_filer_id | string | yes | Filer id from riskmodels_search_filers |
No output schema declared.
No examples provided.
riskmodels_get_hedge_levels RiskModels L1/L2/L3 hedge_levels ~84
Canonical L1, L2, and L3 hedge snapshots (semantic HR/ER + hedge_etfs) from GET /metrics/{ticker}. Use this when you need to compare which cascade depth to trade, distinct from decompose four-bet exposure.
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | Ticker symbol, e.g. NVDA or AAPL |
No output schema declared.
No examples provided.
riskmodels_get_macro_correlation RiskModels Macro Factor Correlation ~135
Exposure of a stock's returns to macro drivers like rates and volatility (POST /correlation). Defaults to the L3 residual return so it isolates idiosyncratic macro sensitivity.
| Name | Type | Req | Description |
|---|---|---|---|
| factors | array | – | Macro factor ids to test (default: standard set) |
| method | string | – | "pearson" (default) or "spearman" |
| return_type | string | – | Return series to correlate (default "l3_residual") |
| ticker | string | yes | Ticker symbol, e.g. NVDA |
| window_days | integer | – | Rolling window in days (default 252) |
No output schema declared.
No examples provided.
riskmodels_get_rankings RiskModels Cross-Sectional Rankings ~104
Where a stock sits in its sector/universe percentile for a given metric (GET /rankings/{ticker}) — peer analytics / manager-skill context.
| Name | Type | Req | Description |
|---|---|---|---|
| cohort | string | – | Peer cohort, e.g. sector or universe |
| metric | string | – | Ranking metric (see riskmodels_get_capability id=rankings) |
| ticker | string | yes | Ticker symbol, e.g. NVDA |
| window | string | – | Lookback window |
No output schema declared.
No examples provided.
riskmodels_get_residual_signal RiskModels Residual Mean-Reversion Signal ~100
Aggregate the L3 residual mean-reversion (stat-arb) signal across a basket (POST /signals/residual-reversion/basket). Optional weights and a minimum signal-quality quintile filter.
| Name | Type | Req | Description |
|---|---|---|---|
| signal_quality_min_quintile | integer | – | Drop names below this signal-quality quintile (1-5) |
| tickers | array | yes | Basket tickers |
| weights | array | – | Optional weights, aligned to tickers |
No output schema declared.
No examples provided.
riskmodels_get_return_attribution RiskModels Return Attribution (factor vs residual) ~194
Daily return attribution (GET /returns-decomposition): decomposes each day's gross return into additive L1/L2/L3 factor (market/sector/subsector) and residual (stock-specific) return components from ds_erm3_returns. Isolates the residual return series — the stock-picking / alpha component — for manager-skill evaluation and stat-arb. Set include_lstar for the Lstar-dispatched residual series.
| Name | Type | Req | Description |
|---|---|---|---|
| include_lstar | boolean | – | Include lstar + lstar_residual_return arrays (default false) |
| market_factor_etf | string | – | Market factor ETF (default SPY) |
| threshold | number | – | Marginal ER threshold for Lstar derivation (default 0.01) |
| ticker | string | yes | Ticker symbol, e.g. NVDA or AAPL |
| years | integer | – | Calendar years of daily history (default 1) |
No output schema declared.
No examples provided.
riskmodels_get_returns RiskModels Stock Total Returns ~130
Daily dividend-adjusted total (gross) return series for any US stock or ETF (GET /ticker-returns), with per-day L3 market/sector/subsector hedge ratios and explained-risk fractions (sum to ~1.0). Up to 15 years of point-in-time, time-safe history. Use for performance tracking, backtests, or as the clean returns input to any risk or attribution work.
| Name | Type | Req | Description |
|---|---|---|---|
| ticker | string | yes | Ticker symbol, e.g. NVDA or AAPL |
| years | integer | – | Years of daily history (default 1, max 15) |
No output schema declared.
No examples provided.
riskmodels_get_schema Get RiskModels Response Schema ~61
Get JSON schema for an API response by path (e.g. ticker-returns-v2.json)
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | Schema path or filename (e.g. ticker-returns-v2.json or /schemas/ticker-returns-v2.json) |
No output schema declared.
No examples provided.
riskmodels_hedge_portfolio RiskModels Portfolio ETF hedge notionals ~74
Batch hedge_ratios at a chosen cascade level (L1/L2/L3), scale HRs by dollar notionals per ticker, and aggregate ETF USD hedge legs.
| Name | Type | Req | Description |
|---|---|---|---|
| level | string | – | Cascade depth; default L3 |
| positions | array | yes | – |
| years | integer | – | – |
No output schema declared.
No examples provided.
riskmodels_hedge_position RiskModels Position Hedge ~61
Scale ETF hedge ratios for a ticker to a dollar position. Returns chart-ready hedge notionals.
| Name | Type | Req | Description |
|---|---|---|---|
| dollars | number | yes | Dollar notional of the stock position |
| ticker | string | yes | Ticker symbol, e.g. NVDA |
No output schema declared.
No examples provided.
riskmodels_list_endpoints List RiskModels API Endpoints ~28
List all public API capabilities (id, name, method, endpoint, short description)
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
riskmodels_portfolio_decompose RiskModels Portfolio Decomposition ~45
Decompose a weighted portfolio into market, sector, subsector, and residual risk layers.
| Name | Type | Req | Description |
|---|---|---|---|
| positions | array | yes | Portfolio positions as ticker plus weight or dollars |
No output schema declared.
No examples provided.
riskmodels_screen_rankings RiskModels Rankings Screen ~149
Full cross-section rank screen (POST /rankings/screen): server-side percentile/decile filtering across the universe for a metric. Use to build screens, not single-ticker lookups.
| Name | Type | Req | Description |
|---|---|---|---|
| as_of | string | – | As-of date (YYYY-MM-DD) |
| cohort | string | yes | Peer cohort |
| decile | integer | – | Restrict to a decile (1-10) |
| limit | integer | – | Max rows (default 100) |
| metric | string | yes | Ranking metric |
| min_percentile | number | – | Minimum percentile filter |
| sector_filter | string | – | Restrict to a sector |
| window | string | yes | Lookback window |
No output schema declared.
No examples provided.
riskmodels_search_etfs RiskModels ETF Search ~81
Find ETFs in the canonical universe by symbol or name (GET /data/etf/search). Free — resolve a hedge/benchmark ETF before pulling its metrics or holdings.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Max results (default 25) |
| q | string | – | Symbol or name fragment, e.g. "semiconductor" or "SMH" |
No output schema declared.
No examples provided.
riskmodels_search_filers RiskModels 13F Filer Search ~88
Find 13F filers by name (GET /13f/filers/search). Free — resolve a manager like "Berkshire" to a bw_filer_id before pulling its snapshot, holdings, or concentration.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Max results (default 25) |
| q | string | yes | Filer name fragment, e.g. "berkshire" |
No output schema declared.
No examples provided.
riskmodels_search_tickers RiskModels Ticker Search ~109
Resolve a symbol or company name to RiskModels tickers (GET /tickers). Free — use this first to turn a name like "Nvidia" into a ticker before any analysis tool. mag7=true returns the Magnificent Seven.
| Name | Type | Req | Description |
|---|---|---|---|
| include_metadata | boolean | – | Include extra metadata per match |
| mag7 | boolean | – | Return the MAG7 set |
| search | string | – | Symbol or company-name fragment, e.g. "nvidia" or "NVDA" |
No output schema declared.
No examples provided.
riskmodels_whitepaper_example RiskModels Live White-Paper Example ~45
Run a live example from the RiskModels white paper. Returns chapter text plus SDK/API output with chart_data.
| Name | Type | Req | Description |
|---|---|---|---|
| exampleId | string | yes | White-paper example id |
No output schema declared.
No examples provided.
What is the RiskModels MCP server?
RiskModels is an MCP server listed in the public MCP registry as io.github.BlueWaterCorp/riskmodels. Dividend-adjusted US equity total returns, risk decomposition, attribution & ETF hedge ratios. This page covers its npm package (@riskmodels/mcp).
Is the RiskModels MCP server safe to use?
RiskModels scores 83 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the RiskModels MCP server expose?
RiskModels exposes 29 tools: riskmodels_decompose, riskmodels_get_returns, riskmodels_get_return_attribution, riskmodels_get_hedge_levels, riskmodels_compare, and 24 more. Their descriptions and schemas cost roughly 2,777 tokens of context every time the server is loaded.
Is the RiskModels MCP server still maintained?
RiskModels is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.