MCP For Claude Marketplace
ELISA Standard Curve Analysis

ELISA Standard Curve Analysis MCP Connector for Claude

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Automated 4-parameter logistic (4PL) regression for ELISA standard curves and sample quantification.

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

This MCP server provides specialized tools for biochemical assay analysis. It uses 4-parameter logistic (4PL) regression to model the sigmoidal relationship between concentration and optical density (OD) in ELISA assays. Users can calculate precise curve parameters, interpolate unknown sample concentrations, evaluate assay precision via replicate analysis, and validate that samples fall within the measurable range of the standard curve. It is designed to handle the non-linear nature of biological responses accurately.

elisa4plregressionbiotechassay

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

interpolate_unknowns

Calculates concentrations for unknown samples based on a fitted 4PL curve

validate_assay_range

Checks if unknown samples are within the valid measurable range of the standard curve

get_curve_parameters

Calculates the mathematical model of the standard curve using 4PL regression

calculate_precision_metrics

Evaluates assay reliability through replicate analysis

See how to talk to your AI agent using ELISA Standard Curve Analysis.

Calculate the parameters for a standard curve with concentrations [0, 1, 10, 100] and ODs [0.05, 0.2, 1.5, 2.8].

The 4PL model parameters are: Minimum (A): 0.048, Maximum (D): 2.85, Inflection Point (C): 12.4, and Hill Slope (B): 0.85. The R-squared value is 0.998.

Interpolate the concentration for an unknown sample with an OD of 0.5 using standards [0, 1, 10, 100] and ODs [0.05, 0.2, 1.5, 2.8].

The interpolated concentration for the sample with OD 0.5 is 3.25 units.

Check if an OD of 3.0 is within the range of standards with ODs [0.05, 0.2, 1.5, 2.8].

No, the OD of 3.0 is out of range as it exceeds the maximum standard OD of 2.8.

The server uses a 4-parameter logistic (4PL) regression model to account for the sigmoidal relationship between concentration and optical density.

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