MCP For Claude Marketplace
Variogram Modeling Analysis

Variogram Modeling Analysis MCP Connector for Claude

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Compute experimental variograms and fit spatial continuity models.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides tools for geostatistical analysis of spatial autocorrelation. It allows AI agents to calculate an experimental variogram using compute_experimental_variogram, fit mathematical models like spherical or exponential via fit_variogram_model, and detect directional variation with detect_anisotropy. It also provides a high-level overview of spatial structures through get_spatial_continuity_summary.

variogramspatial-correlationgeostatisticsanisotropymodeling

4 tools expose this connector's capabilities to your AI agent.

compute_experimental_variogram

Calculates the raw semivariance values for a set of spatial data points at specified intervals

detect_anisotropy

Determines if the spatial correlation varies significantly by direction

fit_variogram_model

Fits a mathematical model to the experimental variogram to derive continuous parameters

get_spatial_continuity_summary

Provides a high-level overview of the spatial structure of the dataset

See how to talk to your AI agent using Variogram Modeling Analysis.

Calculate the experimental variogram for these points: [{'x': 0, 'y': 0, 'z': 10}, {'x': 1, 'y': 1, 'z': 12}, {'x': 2, 'y': 0, 'z': 11}] with a lag distance of 1 and max distance of 5.

[{"lag": 1, "semivariance": 1.33, "pairCount": 2}, {"lag": 2, "semivariance": 0.67, "pairCount": 1}]

Fit a spherical model to these experimental points: [{'lag': 1, 'semivariance': 0.5, 'pairCount': 10}, {'lag': 2, 'semivariance': 1.2, 'pairCount': 8}, {'lag': 3, 'semivariance': 1.8, 'pairCount': 5}].

{"nugget": 0.1, "sill": 2.0, "range": 3.5, "modelType": "spherical"}

Check for anisotropy in this dataset using azimuths 0 and 90 degrees.

{"isAnisotropic": true, "anisotropyRatio": 0.65, "directionalRanges": [{"direction": 0, "range": 10.5}, {"direction": 90, "range": 6.8}]}

It quantifies spatial correlation by calculating semivariance and fitting models to spatial data.

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