Uncertainty Analysis Calculator

Uncertainty Analysis Calculator MCP Connector for Claude

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Quantify measurement uncertainty using statistical propagation and distribution rules.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides specialized tools for calculating measurement uncertainty in analytical results. It handles both Type A uncertainty, derived from statistical analysis of repeated measurements, and Type B uncertainty, derived from external information like calibration certificates. Users can use evaluate_type_a_uncertainty to process observation sets, evaluate_type_b_uncertainty for distribution-based estimates, and calculate_combined_uncertainty to aggregate all sources using the root sum of squares method. Finally, calculate_expanded_uncertainty allows for the determination of confidence intervals using specific coverage factors.

uncertaintystatisticsmeasurementmetrologyanalytical-chemistry

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

calculate_combined_uncertainty

Calculates the total combined standard uncertainty from a list of provided uncertainty sources

calculate_expanded_uncertainty

Calculates the expanded uncertainty to provide a confidence interval

evaluate_type_a_uncertainty

Converts a set of repeated measurement observations into a standard Type A uncertainty

evaluate_type_b_uncertainty

Converts external information into a standard Type B uncertainty

See how to talk to your AI agent using Uncertainty Analysis Calculator.

Calculate the Type A uncertainty for these measurements: 10.1, 10.2, 10.1, 10.3.

The standard uncertainty is 0.0816, with a mean of 10.175 and a standard deviation of 0.0957.

Convert a Type B uncertainty of 0.05 with a rectangular distribution into standard uncertainty.

The standard uncertainty for a rectangular distribution with a value of 0.05 is 0.0289.

Find the expanded uncertainty if the combined standard uncertainty is 0.05 and the coverage factor is 2.

The expanded uncertainty is 0.1.

Type A uncertainty is calculated from the statistical analysis of a series of observations, while Type B uncertainty is based on non-statistical information such as manufacturer specifications or calibration data.

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