MATLAB MCP Server

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The MATLAB MCP Server is the official MathWorks server that enables AI applications to start MATLAB, execute MATLAB code, and assess code quality through the Model Context Protocol. It supports multiple session modes, custom working directories, and both desktop and headless MATLAB operation.

Installation

Prerequisites

• MATLAB R2021a or later installed and added to system PATH
• The server supports MATLAB releases from the past five years

For Claude Code

# Basic installation
claude mcp add --transport stdio matlab -- /path/to/matlab-mcp-server

# With custom working folder
claude mcp add --transport stdio matlab -- /path/to/matlab-mcp-server --initial-working-folder=/home/user/project

# With nodesktop mode
claude mcp add --transport stdio matlab -- /path/to/matlab-mcp-server --matlab-display-mode=nodesktop

For Claude Desktop

1. Install the Filesystem extension in Claude Desktop (Settings > Extensions > Browse extensions)
2. Download matlab-mcp-server.mcpb from the latest release
3. Double-click the .mcpb file and click Install

For VS Code with GitHub Copilot

Create .vscode/mcp.json:

{
    "servers": {
        "matlab": {
            "type": "stdio",
            "command": "/path/to/matlab-mcp-server",
            "args": [
                "--initial-working-folder=/home/user/project",
                "--matlab-display-mode=nodesktop"
            ]
        }
    }
}

Download Binary

Linux/macOS:

# macOS Apple Silicon
curl -L -o ~/Downloads/matlab-mcp-server https://github.com/matlab/matlab-mcp-server/releases/latest/download/matlab-mcp-server-macos-amd64
chmod +x ~/Downloads/matlab-mcp-server

# macOS Intel
curl -L -o ~/Downloads/matlab-mcp-server https://github.com/matlab/matlab-mcp-server/releases/latest/download/matlab-mcp-server-macos-x64
chmod +x ~/Downloads/matlab-mcp-server

Windows: Download from releases page: matlab-mcp-server-windows-x64.exe

Build from source:

go install github.com/matlab/matlab-mcp-server/cmd/matlab-mcp-server@latest

Configuration Arguments

Command-Line Flags

# Specify MATLAB installation
--matlab-root=/usr/local/MATLAB/R2026a

# Initialize MATLAB immediately on startup
--initialize-matlab-on-startup=true

# Set working directory
--initial-working-folder=/home/user/myproject

# Run without MATLAB desktop
--matlab-display-mode=nodesktop

# Session modes
--matlab-session-mode=new        # Always start new MATLAB
--matlab-session-mode=auto       # Connect to existing or start new (default)
--matlab-session-mode=existing   # Only connect to existing MATLAB

Environment Variables

# Equivalent to --matlab-root
export MW_MCP_SERVER_MATLAB_ROOT=/usr/local/MATLAB/R2026a

# Equivalent to --initial-working-folder
export MW_MCP_SERVER_INITIAL_WORKING_FOLDER=/home/user/project

# Equivalent to --matlab-display-mode
export MW_MCP_SERVER_MATLAB_DISPLAY_MODE=nodesktop

# Equivalent to --matlab-session-mode
export MW_MCP_SERVER_MATLAB_SESSION_MODE=existing

Using Existing MATLAB Sessions

For MATLAB R2023a and later:

1. First-time setup:

./matlab-mcp-server --setup-matlab

This installs the MATLAB MCP Server Toolbox.

2. In MATLAB command window:

shareMATLABSession()

Add this to your MATLAB startup.m for automatic sharing:

% In startup.m
shareMATLABSession()

3. Configure MCP server:

claude mcp add --transport stdio matlab -- /path/to/matlab-mcp-server --matlab-session-mode=existing

MCP Tools Available

The server exposes these tools to AI applications:

execute_matlab_code

Execute MATLAB code and return results.

Request:

{
  "name": "execute_matlab_code",
  "arguments": {
    "code": "result = sum([1, 2, 3, 4, 5]); disp(result)"
  }
}

Response:

{
  "content": [
    {
      "type": "text",
      "text": "15"
    }
  ]
}

evaluate_matlab_expression

Evaluate a MATLAB expression and return the result.

Request:

{
  "name": "evaluate_matlab_expression",
  "arguments": {
    "expression": "sqrt(144)"
  }
}

Response:

{
  "content": [
    {
      "type": "text",
      "text": "12"
    }
  ]
}

check_matlab_code

Assess MATLAB code for style and correctness using Code Analyzer.

Request:

{
  "name": "check_matlab_code",
  "arguments": {
    "code": "function y = myFunc(x)\ny = x * 2\nend"
  }
}

Response:

{
  "content": [
    {
      "type": "text",
      "text": "Line 2: Add a semicolon after the statement to hide the output (when it is not the intent)."
    }
  ]
}

Common Usage Patterns

Basic Script Execution

% Simple calculation
A = [1 2 3; 4 5 6; 7 8 9];
eigenvalues = eig(A);
disp(eigenvalues);

Working with Files

% Save data to file
data = rand(100, 3);
save('mydata.mat', 'data');

% Load and process
load('mydata.mat');
mean_values = mean(data);
writematrix(mean_values, 'results.csv');

Plotting and Visualization

% Create and save a plot
x = linspace(0, 2*pi, 100);
y = sin(x);
figure;
plot(x, y);
title('Sine Wave');
xlabel('x');
ylabel('sin(x)');
saveas(gcf, 'sine_plot.png');

Matrix Operations

% Linear algebra operations
A = magic(5);
b = sum(A, 2);
x = A \ b;  % Solve Ax = b

% Check solution
residual = norm(A*x - b);
fprintf('Residual: %.2e\n', residual);

Signal Processing

% Generate and filter signal
Fs = 1000;  % Sampling frequency
t = 0:1/Fs:1-1/Fs;
signal = sin(2*pi*50*t) + 0.5*randn(size(t));

% Apply low-pass filter
[b, a] = butter(6, 100/(Fs/2));
filtered = filter(b, a, signal);

% Compute FFT
Y = fft(filtered);
P2 = abs(Y/length(filtered));
P1 = P2(1:length(filtered)/2+1);

Data Analysis

% Statistical analysis
data = readtable('data.csv');
summary_stats = grpstats(data, 'Category', {'mean', 'std', 'median'});

% Correlation analysis
R = corrcoef(data{:, 2:end});

% Linear regression
mdl = fitlm(data, 'ResponseVar ~ Predictor1 + Predictor2');
disp(mdl);

Custom Functions

% Define reusable function
function [mean_val, std_val] = analyzeData(data)
    mean_val = mean(data, 'omitnan');
    std_val = std(data, 'omitnan');
    
    % Visualize
    figure;
    histogram(data, 30);
    title(sprintf('Mean: %.2f, Std: %.2f', mean_val, std_val));
end

% Use the function
results = rand(1000, 1) * 100;
[m, s] = analyzeData(results);

Simulink Integration

% Load and simulate Simulink model
load_system('mymodel');
simOut = sim('mymodel', 'StopTime', '10');

% Extract and plot results
time = simOut.tout;
output = simOut.yout;
plot(time, output);

Troubleshooting

MATLAB Not Found

Problem: Server cannot locate MATLAB installation.

Solution:

# Explicitly specify MATLAB root
--matlab-root=/Applications/MATLAB_R2026a.app  # macOS
--matlab-root=/usr/local/MATLAB/R2026a         # Linux
--matlab-root=C:\\Program Files\\MATLAB\\R2026a  # Windows

# Or set environment variable
export MW_MCP_SERVER_MATLAB_ROOT=/usr/local/MATLAB/R2026a

Connection to Existing Session Fails

Problem: Cannot connect with --matlab-session-mode=existing

Solution:

1. Ensure MATLAB MCP Server Toolbox is installed:

./matlab-mcp-server --setup-matlab

2. In MATLAB, run:

shareMATLABSession()

3. Verify connection status:

status = shareMATLABSession('status')

Path Issues

Problem: MATLAB cannot find scripts or data files.

Solution:

% Check current directory
pwd

% Change directory
cd('/path/to/project')

% Add to path
addpath('/path/to/scripts');
addpath(genpath('/path/to/project'));  % Include subdirectories

Graphics/Desktop Issues

Problem: Commands requiring GUI fail in nodesktop mode.

Solution: Graphics commands still work in nodesktop mode, but if issues persist:

# Switch to desktop mode
--matlab-display-mode=desktop

Memory Issues

Problem: Out of memory errors with large datasets.

Solution:

% Clear workspace
clear all

% Close figures
close all

% Use memory-efficient operations
% Instead of loading entire file:
data = load('largefile.mat');

% Use memory mapping:
m = memmapfile('largefile.dat', 'Format', 'double');

Code Execution Timeout

Problem: Long-running code appears to hang.

Solution:

% Add progress indicators
for i = 1:1000
    % Process
    if mod(i, 100) == 0
        fprintf('Progress: %d/1000\n', i);
    end
end

% Use parallel processing for large tasks
parfor i = 1:1000
    % Parallel computation
end

Version Compatibility

Problem: Functions not available in older MATLAB versions.

Solution:

% Check MATLAB version
ver('MATLAB')

% Conditional code based on version
if verLessThan('matlab', '9.10')  % R2021a
    warning('Some features require R2021a or later');
end

Advanced Configuration

Custom Tools Extension

Create custom MCP tools by providing a JSON extension file:

--extension-file=/path/to/my-tools.json

For details, see the Custom Tools Guide.

Multiple MATLAB Versions

# Development with latest MATLAB
claude mcp add --transport stdio matlab-dev -- /path/to/matlab-mcp-server --matlab-root=/usr/local/MATLAB/R2026a

# Production with stable MATLAB
claude mcp add --transport stdio matlab-prod -- /path/to/matlab-mcp-server --matlab-root=/usr/local/MATLAB/R2024b

Project-Specific Configuration

For VS Code, use workspace-specific .vscode/mcp.json:

{
    "servers": {
        "matlab": {
            "type": "stdio",
            "command": "/path/to/matlab-mcp-server",
            "args": [
                "--initial-working-folder=${workspaceFolder}",
                "--matlab-display-mode=nodesktop",
                "--initialize-matlab-on-startup=true"
            ]
        }
    }
}

Resources

• GitHub Repository
• MATLAB Agentic Toolkit
• Simulink Agentic Toolkit
• MathWorks AI Community
• Model Context Protocol Specification