MCP For Claude Marketplace
Flow Cytometry Analysis

Flow Cytometry Analysis MCP Connector for Claude

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Analyze fluorescence-based flow cytometry data, calculate cell population metrics, and apply spectral compensation.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides specialized tools for processing and analyzing flow cytometry data. It allows AI agents to perform complex biological data tasks such as calculating cell population percentages and MFI using analyze_populations, correcting spectral overlap with apply_compensation, and determining non-specific binding via evaluate_isotype_background. It also provides granular distribution metrics through get_population_statistics to support detailed immunological research.

flow-cytometryfluorescenceimmunologystatisticsbiotechnology

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

evaluate_isotype_background

Determines the level of non-specific binding to establish a baseline for true fluorescence

analyze_populations

Calculates the percentage and statistical metrics for defined cell populations

apply_compensation

Adjusts fluorescence data to correct for spectral overlap between fluorophores

get_population_statistics

Provides detailed distribution metrics for a specific gated subset

See how to talk to your AI agent using Flow Cytometry Analysis.

Calculate the population statistics for my fluorescence data using this gating strategy.

The analysis shows that the T-cell population accounts for 15.4% of the total events with an MFI of 450.2.

Apply compensation to this raw fluorescence data.

The fluorescence data has been corrected for spectral overlap based on the provided matrix.

Is the signal from my target antibody significant compared to the isotype control?

Yes, the signal is significant as the target MFI exceeds the isotype MFI by more than the required threshold.

You can use the `apply_compensation` tool by providing your raw fluorescence measurements and a valid compensation matrix.

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