The FEA-MCP Server enables AI-driven interaction with FEA software, supporting geometric modeling, object creation, and data retrieval across multiple platforms including ETABS and LUSAS, via a unified API interface.
Added on:
Created by:
Apr 27 2025
The FEA-MCP Server enables AI-driven interaction with FEA software, supporting geometric modeling, object creation, and data retrieval across multiple platforms including ETABS and LUSAS, via a unified API interface.
Added on:
Created by:
Apr 27 2025
Apostolos Grammatopoulos
Featured
What is FEA-MCP Server?
The FEA-MCP Server offers a comprehensive API to facilitate AI-controlled finite element analysis (FEA) processes. It supports multiple mainstream FEA packages such as ETABS and LUSAS by providing functions for geometric modeling, object creation, and data retrieval. Users can generate points, lines, surfaces, and volumes, and extract model data seamlessly. Future enhancements include model management and analysis control, making it a powerful tool for automation and AI integration in structural analysis workflows.
Who will use FEA-MCP Server?
- Structural Engineers
- Researchers in Finite Element Analysis
- Developers of FEA automation tools
- Academics in Civil/Mechanical Engineering
How to use the FEA-MCP Server?
- Step 1: Install the required Python libraries and download the server files.
- Step 2: Configure the server settings including FEA software version.
- Step 3: Launch the MCP server using the specified command.
- Step 4: Connect your AI client or automation script to the server.
- Step 5: Use the provided API functions to model, analyze, and retrieve FEA data.
FEA-MCP Server's Core Features & Benefits
The Core Features
- get_units
- create_objects_by_coordinates
- get_all_geometries
- get_points
- get_frames (ETABS)
- get_areas (ETABS)
- get_lines (LUSAS)
- get_surfaces (LUSAS)
- get_volumes (LUSAS)
- sweep_points
- sweep_lines
- sweep_surfaces
- select
The Benefits
- Automates FEA modeling and analysis tasks through AI integration
- Supports multiple leading FEA software packages with unified API
- Simplifies geometric model creation and data extraction
- Enables scalable and repeatable FEA workflows
FEA-MCP Server's Main Use Cases & Applications
- Automated structural analysis for civil engineering projects
- AI-driven FEA model creation and modification
- Research simulations involving model data retrieval
- Educational tools for teaching finite element analysis
FAQs of FEA-MCP Server
Developer
- GreatApo
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.
Virtualization
A Python-based MCP setup that allows quick deployment of weather data services for MCP hosts and clients.
A JavaScript/TypeScript-based MCP client for integrating and managing multiple services efficiently.
A client implementation to connect and interact with MCP servers, enabling tool discovery and remote service integration.
A command-line interface for interacting with MCP servers via stdio and HTTP transport, simplifying server communication.
A TypeScript client for interacting with MCP servers, supporting JSON-RPC requests and specialized services.
Simple MCP server enabling shell execution, local connectivity via Ngrok, and Docker-based Ubuntu24 container hosting.
A tool to connect AI agents to remote MCP servers, enabling tool discovery, authentication, and resource integration.
A Java-based MCP server for managing Minecraft modpack configurations and server operations.
A desktop application using Compose Multiplatform that connects to MCP servers for weather and game data management.