MatlabMCP is a Model Context Protocol server that allows clients like LLMs to run MATLAB code, retrieve variables, and communicate structured results through a shared MATLAB session, enhancing automation and integration with MATLAB environment.
Added on:
Created by:
Apr 09 2025
MatlabMCP is a Model Context Protocol server that allows clients like LLMs to run MATLAB code, retrieve variables, and communicate structured results through a shared MATLAB session, enhancing automation and integration with MATLAB environment.
Added on:
Created by:
Apr 09 2025
Jigar Bhoye
Featured
What is MatlabMCP?
MatlabMCP serves as an interface for large language models and other clients to execute MATLAB code and manage MATLAB workspace variables seamlessly. It leverages the MATLAB Engine API for Python to run arbitrary MATLAB snippets asynchronously, fetch variable states, and handle structured data communication. This server supports integration with AI agents, automates MATLAB workflows, and provides a shared MATLAB session for collaborative tasks. It requires MATLAB R2023a+, Python 3.12+, and the MATLAB Engine API, enabling efficient and non-blocking execution of MATLAB commands and data exchange for research, automation, and development purposes.
Who will use MatlabMCP?
- AI researchers
- MATLAB users
- Developers integrating MATLAB with LLMs
- Automation engineers
- Data scientists
How to use the MatlabMCP?
- Step 1: Install MATLAB and configure shared engine with `matlab.engine.shareEngine`
- Step 2: Clone the MatlabMCP repository from GitHub
- Step 3: Set up Python environment and install dependencies via `uv pip sync`
- Step 4: Run the MCP server using `main.py`
- Step 5: Connect clients (like LLMs) to send MATLAB code execution requests and receive structured responses
MatlabMCP's Core Features & Benefits
The Core Features
- runMatlabCode
- getVariable
The Benefits
- Enables remote MATLAB code execution
- Structured JSON communication
- Asynchronous non-blocking calls
- Supports workspace variable management
MatlabMCP's Main Use Cases & Applications
- Automated MATLAB script execution for research
- Integration of MATLAB computational tasks into AI workflows
- Remote MATLAB workspace management for data analysis
- Automated testing and simulation with MATLAB via AI agents
FAQs of MatlabMCP
Developer
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
AI Chatbot
Integrates APIs, AI, and automation to enhance server and client functionalities dynamically.
Provides long-term memory for LLMs by storing and retrieving contextual information via MCP standards.
An advanced clinical evidence analysis server supporting precision medicine and oncology research with flexible search options.
A platform collecting A2A agents, tools, servers, and clients for effective agent communication and collaboration.
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
PHP client library enabling interaction with MCP servers via SSE, StdIO, or external processes.
A platform for managing and deploying autonomous agents, tools, servers, and clients for automation tasks.
Enables interaction with powerful Text to Speech and video generation APIs for multimedia content creation.
An MCP server providing API access to RedNote (XiaoHongShu, xhs) for seamless integration.