MATLAB MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MATLAB MCP Servergenerate a MATLAB script to plot a sine wave"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MATLAB MCP Server

We welcome contributions from everyone.
Related MCP server: MATLAB MCP Server
A powerful MCP server that integrates MATLAB with AI, allowing you to execute MATLAB code, generate MATLAB scripts from natural language descriptions, and access MATLAB documentation directly through your AI assistant.
Features
Resources
Access MATLAB documentation via
matlab://documentation/getting-startedURIGet started guide with examples and usage instructions
Tools
execute_matlab_code- Execute MATLAB code and get resultsRun any MATLAB commands or scripts
Option to save scripts for future reference
View output directly in your conversation
generate_matlab_code- Generate MATLAB code from natural languageDescribe what you want to accomplish in plain language
Get executable MATLAB code in response
Option to save generated scripts
Development
Install dependencies:
npm installBuild the server:
npm run buildFor development with auto-rebuild:
npm run watchRequirements
MATLAB installed on your system
Node.js (v14 or higher)
Installation
Installing via Smithery
To install MATLAB MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @WilliamCloudQi/matlab-mcp-server --client claude1. Install the package
npm install -g matlab-mcp-serverOr clone the repository and build it yourself:
git clone https://github.com/username/matlab-mcp-server.git
cd matlab-mcp-server
npm install
npm run build2. Configure cline to use the server
To use with cline , add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"matlab-server": {
"command": "node",
"args": ["/path/to/matlab-server/build/index.js"],
"env": {
"MATLAB_PATH": "/path/to/matlab/executable"
},
"disabled": false,
"autoApprove": []
}
}
}Replace /path/to/matlab/executable with the path to your MATLAB executable:
Windows: Usually
C:\\Program Files\\MATLAB\\R2023b\\bin\\matlab.exemacOS: Usually
/Applications/MATLAB_R2023b.app/bin/matlabLinux: Usually
/usr/local/MATLAB/R2023b/bin/matlab
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspectorThe Inspector will provide a URL to access debugging tools in your browser.
Available Tools
2 toolsexecute_matlab_codeC
Execute MATLAB code and return the results
Inputs: code (required), saveScript, scriptPath.
generate_matlab_codeC
Generate MATLAB code from a natural language description
Inputs: description (required), saveScript, scriptPath.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
TDQS
Scored across 2 tools
The two tools are clearly distinct: one generates MATLAB code and the other executes it. There is no ambiguity or overlap in their purposes.
Both tool names follow the same verb_noun pattern: generate_matlab_code and execute_matlab_code. The naming is perfectly consistent and predictable.
Two tools is on the low end and feels thin for a server, but each tool has a meaningful role. The set is coherent, yet minimal.
The core workflow of generating and executing MATLAB code is covered without dead ends. Some auxiliary capabilities like persistent workspace management or file I/O are missing, but agents can likely work around these with generated code.
Maintenance
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