V-Lab MCP

Financial-risk data from NYU Stern's Volatility and Risk Institute: volatility, SRISK, CRISK, COVOL, ILLIQ, climate benchmarks, and long-run VaR, exposed as MCP tools backed by published academic research. **39 tools across 8 domains:** - **Volatility** — global map, country/sector/industry breakdowns, individual asset time series - **Systemic risk (SRISK)** — firm-level capital shortfall under market stress, country and global rankings - **Climate risk (CRISK)** — capital shortfall under a climate-factor shock, with climate-beta breakdowns - **COVOL** — common volatility / synchronized stress across global assets, with PC1 loadings and CAV - **Liquidity (ILLIQ)** — Amihud illiquidity composites, sector-level changes, top movers - **Long-run VaR** — 30-day and 365-day potential-loss estimates across percentiles - **Climate benchmarks** — factor-portfolio returns, volatility, and correlations - **Discovery** — search across assets, analyses, and datasets OAuth 2.1 + PKCE; free V-Lab account; no API key required. Streamable HTTP transport. **Documentation:** - [Setup guide](https://vlab.stern.nyu.edu/setup-mcp): connect Claude Desktop, Claude.ai, the Anthropic Workbench, the MCP Inspector, or any OAuth 2.1 + PKCE-capable client - [Tool reference](https://vlab.stern.nyu.edu/docs/mcp): every tool with parameters, return shapes, and example invocations > *V-Lab data is academic research output. Please cite V-Lab when used in published work or public-facing content.*

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接入信息

传输形态: http
鉴权方式: 鉴权未知
端点: https://vlab.run.tools

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{
  "mcpServers": {
    "V-Lab MCP": {
      "url": "https://vlab.run.tools"
    }
  }
}

能力清单

工具	说明
server.info	Get information about the V-Lab MCP server including capabilities, status, and available features
search.assets	Resolve a financial asset by ticker, name, FIGI, SEDOL, or GVKEY. Returns compact results (ticker, name, active, last_result_date). Pass `include_analyses:true` for the full analyses catalog.
search.datasets	Search for datasets and discover their constituent assets and available analyses. Returns datasets matching the query along with paginated asset lists and analysis information.
search.asset_in_dataset	Check if a specific asset is a constituent of a dataset and retrieve available analyses for that combination.
search.analyses	Search for analyses by application, model, or memo. Returns flat results with full context for each analysis instance.
volatility.get	Annualized volatility time series for an asset (GARCH-family models).
liquidity.get	Get liquidity time series data for an asset. Returns illiquidity measures from ILLIQ models. SMEM and MFMEM models also include long-term trend data.
volatility.params	Latest estimated GARCH-family parameters for an asset (omega, alpha, beta, gamma, etc.), each with its standard error, plus model persistence and half-life. One parameter set per analysis — the most recent successful fit; there is no parameter history.
volatility.forecast	Dynamically-generated multi-step volatility forecast (the cumulative-average annualized term structure) at user-defined horizons. Computed by iterating the fitted model forward — matching the V-Lab website's forecast chart — so any steps-ahead can be requested, not just the stored 1d/1w/1m/6m/1y points. Multi-factor models (MF2-GARCH) are interpolated across the stored summary forecasts.
liquidity.params	Latest estimated liquidity (MEM / ILLIQ-family) parameters for an asset, each with its standard error, plus model persistence and half-life. Vector parameters (e.g. spline knot coefficients) are returned as arrays. One parameter set per analysis — the most recent successful fit; there is no parameter history.
liquidity.forecast	Dynamically-generated multi-step illiquidity (ILLIQ) forecast (the cumulative-average term structure) at user-defined horizons. Computed by iterating the fitted model forward — matching the V-Lab website's forecast chart — so any steps-ahead can be requested. Multi-factor models (ILLIQ-MFMEM) are interpolated across the stored summary forecasts.
liquidity.illiq_composite	Get the ILLIQ Composite market-wide liquidity index. This time series shows aggregate market liquidity conditions based on market-cap weighted average of individual ILLIQ measures. Higher values indicate less liquid markets.
liquidity.list_change_countries	List countries that have aggregated sector-change data — the input universe for `liquidity.changes`. Returns each country with its asset count. Note: this is not the universe of every country with ILLIQ coverage; per-asset tools like `liquidity.get` and `liquidity.movers` work on a broader universe.
liquidity.changes	Get sector-level liquidity statistics for a country. Shows which GICS sectors are experiencing liquidity stress (deteriorating) or improvement.
liquidity.movers	Get assets with highest illiquidity ("hot") or fastest deteriorating liquidity ("heating"). Use to identify liquidity-stressed assets.
volatility.global_map	Get relative volatility percentiles for all countries. Supports single-date snapshots OR time series with `start_date`/`end_date`. Data available from 1990 to present. Drill down: `volatility.country.get` (sectors) or `volatility.country.summary` (key indices).
volatility.country.get	Get GICS sector/industry volatility breakdown for a specific country. Without `industry` param: returns sectors. With `industry` param (e.g. `"20"`): returns sub-industries. Drill down: `volatility.country.industries` (individual assets within an industry).
volatility.country.summary	Get market summary for a country showing key indices with current volatility levels and changes, grouped by market type (Equities, Currencies, etc.). Drill down: `volatility.get` (full time series for any asset).
volatility.country.industries	Get individual assets within a GICS industry for a country, with relative volatility percentiles and levels. Use after `volatility.country.get` to drill down from sector/industry to individual assets. Part of the volatility hierarchy.
climate_benchmarks.list	List available climate risk benchmarks. These are V-Lab's proprietary climate factor portfolios including Stranded Assets, Emissions Factor, Oil Beta Factor, and Subsidy Factor.
climate_benchmarks.returns	Get returns time series for a climate benchmark. Returns cumulative returns by default (base 100), or daily returns if cumulative=false.
climate_benchmarks.volatility	Get annualized volatility time series for a climate benchmark.
climate_benchmarks.correlations	Get correlation matrix between all available climate benchmarks.
climate.categories	List the climate-fund category taxonomy — the ESG / low-carbon "groups" V-Lab classifies funds into (e.g. Broad ESG, Low Carbon, Sustainable Sector, Fossil Fuel Free, Carbon Trading) — with the number of active funds in each. Use it to discover the valid values for `climate.assets`'s `categories` filter. A fund may belong to more than one category.
climate.assets	List V-Lab's climate-fund universe — ESG / low-carbon ETFs and mutual funds — each with its categories and trailing 1-year analytics (annualized volatility and return). Optionally restrict to one or more categories. Distinct from `climate_benchmarks.*`, which are factor portfolios, not investable funds. Use `climate.categories` to discover the category names.
srisk.list	List available SRISK (systemic risk) analyses with regions and coverage. Part of the SRISK hierarchy: `srisk.list` → `srisk.ranking` → `srisk.country` → `srisk.firm`.
srisk.ranking	Get top entities ranked by SRISK (systemic risk). Can rank firms (default), countries, regions (continents), or markets. Includes concentration metrics (HHI, top-N share). Part of the SRISK hierarchy: `srisk.list` → `srisk.ranking` → `srisk.country` → `srisk.firm`. Data note: SRISK relies on balance sheet data which may arrive with a lag; values for recent quarters may be revised as updates are received from data providers.
srisk.country	Get SRISK data for a specific country. Returns either firm rankings (default) or country-level time series with `time_series=true`. Part of the SRISK hierarchy: `srisk.list` → `srisk.ranking` → `srisk.country` → `srisk.firm`.
srisk.firm	Get SRISK time series for a specific firm. Part of the SRISK hierarchy: `srisk.list` → `srisk.ranking` → `srisk.country` → `srisk.firm`.
srisk.movers	Get firms with largest SRISK changes over a period. Returns top increases and/or decreases with change attribution (debt/equity/risk breakdown). Part of the SRISK hierarchy for identifying risk trends.
crisk.list	List available CRISK (climate risk) analyses with coverage. CRISK is the climate-stress analog of SRISK, measuring expected capital shortfall under a climate-risk factor shock. Part of the CRISK hierarchy: `crisk.list` → `crisk.ranking` → `crisk.country` → `crisk.firm`.
crisk.ranking	Get top entities ranked by CRISK (climate-stress capital shortfall). Can rank firms (default), countries, regions (continents), or markets. Includes concentration metrics (HHI, top-N share). Part of the CRISK hierarchy: `crisk.list` → `crisk.ranking` → `crisk.country` → `crisk.firm`. Data note: CRISK relies on balance sheet data which may arrive with a lag; values for recent quarters may be revised as updates are received from data providers.
crisk.country	Get CRISK data for a specific country. Returns either firm rankings (default) or country-level time series with `time_series=true`. Part of the CRISK hierarchy: `crisk.list` → `crisk.ranking` → `crisk.country` → `crisk.firm`.
crisk.firm	Get CRISK time series for a specific firm. CRISK is computed from components (climate beta, market cap, book assets, book equity) using a 50% climate stress shock. Part of the CRISK hierarchy: `crisk.list` → `crisk.ranking` → `crisk.country` → `crisk.firm`.
crisk.movers	Get firms with largest CRISK changes over a period. Returns top increases and/or decreases with change attribution (debt/equity/risk breakdown). Part of the CRISK hierarchy for identifying climate risk trends.
covol.list	List available COVOL (common volatility) analyses with coverage. COVOL extracts a synchronized-stress factor from the cross-section of daily returns within each dataset. Each analysis covers a different universe (e.g., country ETFs, asset classes, commodities). Part of the COVOL hierarchy: `covol.list` → `covol.summary` → `covol.get`.
covol.summary	COVOL stress snapshot: composite PC1 plus per-analysis levels across every available COVOL analysis.
covol.composite	Get Composite COVOL Index time series. Returns the systematic stress component (PC1) with daily factor loadings showing how each analysis contributes to market-wide stress.
covol.cav	Get COVOL-Adjusted Volatility (CAV) time series for each analysis and aggregate (ACAV). CAV is the annualized risk of the common factor within each analysis. ACAV combines all four into a single portfolio-level risk metric.
covol.get	Get COVOL Index time series for a specific analysis. Use `covol.list` to discover the available analyses and their memo strings.
covol.loadings	Get asset loadings (factor sensitivities) for a COVOL analysis. Shows how much each asset contributes to common volatility, both equal-weighted and variance-weighted.
covol.events	Get top COVOL events (highest stress dates) for an analysis with z-scores and event descriptions. Events include major market crashes, geopolitical events, and policy shocks.
lrvar.summary	Current Long-Run VaR across all horizons and percentiles (decimals, e.g., -0.1435 = 14.35% loss). Returns LRGJRF (return-series) and/or LRGJROF (options-augmented) where available.
lrvar.get	Long-Run VaR time series for an analysis (decimals, e.g., -0.1435 = 14.35% loss). Horizons: 30d (tactical) or 365d (strategic). Percentiles: 1 or 5.
feedback.submit	Report feedback on V-Lab MCP to help improve the server. TWO SHAPES ARE SUPPORTED: 1. Tool rating — pass tool_name + helpful (+ optional message): { tool_name: "volatility.get", helpful: true, message: "Data was clear and correct" } { tool_name: "srisk.ranking", helpful: false, message: "aggregate_by=firm returned a DB error" } 2. General feedback — pass category + message (no tool_name required): { category: "bug_report", message: "covol.cav is listed in server_info but has no tool schema" } { category: "feature_request", message: "Add a tool that compares volatility across multiple assets" } { category: "data_request", message: "Need coverage of Brazilian small-cap banks" } { category: "general", message: "Overall very useful for market-state summaries" } WHEN TO USE: - After completing a task, if you have meaningful input on a specific tool (helpful=true/false). - Any time to file a bug, request a feature, request data coverage, or share general feedback — no tool name required.

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