Quality Control Chart Design

Quality Control Chart Design MCP Connector for Claude

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Designs statistical process control charts to monitor process stability.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides essential tools for Statistical Process Control (SPC). It allows AI agents to calculate control limits, identify center lines, and detect out-of-control patterns in manufacturing or service processes. Using tools like calculate_control_parameters and analyze_process_stability, agents can determine if a process is stable or if it exhibits non-random trends and shifts.

spcquality-controlstatisticsmanufacturingprocess-stability

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

analyze_process_stability

Determines if a process is in a state of statistical control based on provided measurements and chart type

calculate_control_parameters

Generates the mathematical boundaries for a specific SPC chart type

generate_individual_limits

Specifically calculates limits for processes where measurements are taken one at a time (Individual charts)

detect_out_of_control_patterns

Identifies specific non-random patterns in a sequence of data points

See how to talk to your AI agent using Quality Control Chart Design.

Calculate the control limits for these subgroups: [[10, 12], [11, 13], [9, 11]] using an x_bar chart.

The calculated parameters for the x_bar chart are: UCL: 13.5, LCL: 8.5, and Center Line: 11.0.

Is this process stable? Measurements: [10, 10, 10, 15, 10], chartType: 'individual', controlLimits: {"ucl": 12, "lcl": 8}, centerLine: 10

The process is unstable. A violation was detected because the measurement 15 falls outside the upper control limit of 12.

Find patterns in this series: [10, 11, 12, 13, 14, 15], centerLine: 10, ucl: 20, lcl: 0

A trend pattern was detected in the series.

You can design X-bar, R, S, and Individual (I) charts using the `calculate_control_parameters` and `generate_individual_limits` tools.

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