CalculiX MCP logo

CalculiX MCP

Community
Cai-aa

Open-source FEM solver (ccx) as a FastMCP server, integrated into the CAE-Agent-Hub agent + browser-viewer ecosystem

PublisherCai-aa
RepositoryCAE-Agent-Hub
LanguagePython
Forks
119
Stars
938
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    CalculiX MCP exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    938 stars and 119 forks from the linked repository.

CAE Agent Hub

Language: English | 中文

CAE Agent Hub is a collection of MCP servers, reusable agent skills, solver automation workflows, and browser-based result viewers for engineering simulation. It is designed to let AI coding clients such as Codex, Cursor, Claude Code, and Claude Desktop work with installed CAE applications and engineering solvers instead of producing only offline examples.

What is included

The current repository provides:

  • MCP servers for Abaqus/CAE, ANSYS Fluent, ANSYS Workbench/Mechanical, Ansys Electronics Desktop/HFSS, Altair HyperWorks, LAMMPS, OVITO, CalculiX, and the FreeCAD → Elmer FEM → ParaView FEP Agent Hub workflow.
  • Reusable Skills for Abaqus modeling, setup, analysis, execution, postprocessing, optimization, and reference workflows, together with evidence-oriented workflows for several CAE ecosystems.
  • Subagent resources stored under Subagent/.
  • Solver automation and supporting assets/models stored under assets/ and models/.
  • The original Text to CAE browser viewer for inspecting lightweight result_mesh.json simulation results.
  • Examples, tests, templates, and documentation intended to keep solver binaries, licenses, private paths, and generated results out of source control.

The repository still contains some historical text-to-cae naming for compatibility with existing viewer cases.

Repository

text
https://github.com/Cai-aa/CAE-Agent-Hub

Architecture

text
AI client
   │
   ├── MCP server
   │      │
   │      └── live CAE application / solver
   │
   └── Skill / Subagent
          │
          └── modeling / setup / solving / validation workflow
                         │
                         ▼
                  native solver results
                         │
                         ▼
                lightweight result export
                         │
                         ▼
                browser viewer / report workflow

The repository separates responsibilities:

  • MCP servers provide tool access to installed CAE applications and solvers.
  • Skills provide reusable instructions for modeling, setup, solving, postprocessing, optimization, and validation.
  • Subagent resources support task decomposition and specialized agent workflows.
  • CAE applications and solvers perform the actual engineering calculations.
  • Viewer modules inspect exported result data without requiring the solver to remain open.

MCP Index

MCPStatusPurposeMain entry pointsTrigger keywords
Abaqus MCPActiveConnect MCP clients to a live Abaqus/CAE session through a local TCP bridge; run Python in the Abaqus kernel, inspect models, submit jobs, monitor status, inspect ODB files, and capture viewport images.mcp_server.py, abaqus_mcp_plugin.py, abaqus_plugins/mcp_control/Abaqus MCP, Abaqus/CAE, ODB, viewport, submit job, live Abaqus
ANSYS Fluent MCPActiveDetect Fluent, launch batch journals, track jobs/logs, and optionally manage live PyFluent sessions for Scheme, TUI, and Python probes.server.py, tools/fluent_bridge.py, tools/pyfluent_session.pyFluent, PyFluent, journal, TUI, CFD, Scheme
ANSYS Workbench MCPActiveControl Workbench and Mechanical through Python helpers plus an ACT bridge, with file-queue and socket-timer communication modes.server.py, tools/, workbench_plugin/Workbench, Mechanical, ACT, LS-DYNA, socket timer
Ansys AEDT MCPActiveConnect MCP clients to Ansys Electronics Desktop / HFSS through a raw TCP JSON bridge; inspect projects, create HFSS designs, save projects, and run small AEDT Python snippets.mcp_server.py, aedt_mcp_bridge.py, scripts/install_aedt_toolkit_button.ps1AEDT, HFSS, Electronics Desktop, antenna, S-parameters
Altair HyperWorks MCPActiveControl HyperWorks and a live HyperMesh session through typed, workspace-scoped tools plus an authenticated in-application Python bridge; inspect models and entities, run screened batch Tcl, and manage solver jobs.src/hyperworks_mcp/server.py, hyperworks_extension/, install_hyperworks_extension.ps1HyperWorks, HyperMesh, HyperView, OptiStruct, Radioss, live Python bridge
LAMMPS MCPActiveDetect a local LAMMPS executable, run explicit input decks, and retain job evidence.server.py, tools/atomistic_bridge.pyLAMMPS, molecular dynamics, trajectory
OVITO MCPActiveDetect OVITO scripting support and run explicit postprocessing scripts with evidence logs.server.py, tools/atomistic_bridge.pyOVITO, atomistic, visualization
CalculiX MCPActiveWrap the open-source CalculiX FEM solver (ccx): parse .inp decks, edit design variables, run ccx, read .dat results, export result_mesh.json, extract natural frequencies and viewer-renderable mode shapes, and run two-stage sizing optimization.mcp_server.py, tools/inp_parser.py, tools/solver.py, tools/result_exporter.py, tools/optimizer.pyCalculiX, FEM, ccx, .inp, .dat, .frd, von Mises, design variables, sizing optimization, modal analysis, resonance
FEP Agent HubActiveCoordinate independent FreeCAD CAD, Elmer FEM, and ParaView postprocessing MCP servers. Includes verified thermal, electromagnetic, structural, and laminar-flow profiles with evidence gates.mcp/*/src/*_mcp/server.py, scripts/protocol_smoke.py, scripts/mcp_full_validation.pyFreeCAD, Elmer FEM, ParaView, FEP, heat, transformer, beam, laminar flow, Lenz law

Adding a new MCP should follow the repository pattern: keep reusable source, examples, tests, and bilingual README files together, while excluding virtual environments, solver results, private paths, licenses, and generated project data.

Skill Index

The repository contains an Abaqus master router and specialized workflow skills, plus evidence-oriented workflows for other CAE ecosystems.

Abaqus

SkillStatusPurpose
abaqusActiveMaster router for Abaqus FEA scripting and analysis workflows.
abaqus-geometryActiveCreate parts, sketches, extrusions, assemblies, and import CAD.
abaqus-materialActiveDefine materials, sections, density, elasticity, plasticity, and common engineering properties.
abaqus-meshActiveGenerate finite element meshes and choose element types.
abaqus-interactionActiveDefine contact, friction, tie constraints, connectors, and bonded surfaces.
abaqus-amplitudeActiveDefine time-varying amplitudes for ramp, pulse, cyclic, or transient loads.
abaqus-bcActiveDefine boundary conditions such as fixed, pinned, clamped, displacement, and symmetry constraints.
abaqus-docsActiveDownload and manage abqpy / Abaqus API documentation.
abaqus-fieldActiveDefine initial conditions and predefined fields such as initial temperature or residual stress.
abaqus-loadActiveApply concentrated forces, pressures, gravity, and distributed loads.
abaqus-outputActiveConfigure field and history output requests.
abaqus-stepActiveDefine analysis steps, procedures, increments, time periods, and nonlinear geometry settings.
abaqus-static-analysisActiveComplete static structural workflow for stress, displacement, reactions, strength, and stiffness.
abaqus-modal-analysisActiveExtract natural frequencies and mode shapes for vibration and resonance checks.
abaqus-dynamic-analysisActiveComplete dynamic workflow for impact, crash, drop test, transient, explicit, or implicit dynamics.
abaqus-thermal-analysisActiveHeat transfer workflow for steady-state or transient temperature distribution.
abaqus-coupled-analysisActiveCoupled thermomechanical workflow for thermal stress and temperature-driven deformation.
abaqus-contact-analysisActiveMulti-body contact workflow for friction, press fit, bolts, and assemblies.
abaqus-fatigue-analysisActiveFatigue and durability workflow for cycles, damage accumulation, and life prediction.
abaqus-jobActiveCreate, submit, monitor, and manage Abaqus jobs and input files.
abaqus-exportActiveExport Abaqus geometry and results to STL, STEP, CSV, INP, or external formats.
abaqus-odbActiveRead ODB results and extract stress, displacement, reaction force, and result summaries.
abaqus-optimizationActiveConfigure Tosca optimization responses, objectives, constraints, and SIMP-style settings.
abaqus-shape-optimizationActiveOptimize fillet/notch/surface shape to reduce peak stress without topology removal.
abaqus-topology-optimizationActiveTopology optimization workflow for reducing mass while preserving stiffness.

Cross-ecosystem and evidence-oriented workflows

SkillStatusPurpose
fea-structuralReferenceGeneral structural FEA guidance across static, dynamic, nonlinear, and validation domains.
fenics-femReferenceFEniCS/dolfinx reference for weak forms, gmsh meshes, PDEs, and ParaView export.
lammps-evidence-mdActiveEvidence-first LAMMPS molecular-dynamics workflow.
ovito-evidence-postprocessingActiveEvidence-first OVITO atomistic postprocessing workflow.
ansys-mechanical-evidence-structuralActiveMechanical evidence and acceptance gates, complementary to the Workbench workflow skill.
aedt-evidence-electromagneticsActiveGeneric AEDT evidence workflow with Maxwell checks.
comsol-motor-nvh-evidenceActiveCheckpointed permanent-magnet motor NVH workflow coupling rotating electromagnetics, structural modes, acoustics, and Campbell validation.
calculix-femActiveWorkflow for driving the CalculiX MCP, including .inp inspection, variable editing, solving, result extraction, and viewer export.
calculix-sizing-optimizationActiveTwo-stage sizing optimization using LHS sweep and coordinate descent under stress/displacement or natural-frequency constraints.
calculix-modal-analysisActiveNatural frequencies and mode shapes from a CalculiX *FREQUENCY step, with viewer export.
fep-agent-hubActiveEvidence-first router for FreeCAD → Elmer FEM → ParaView workflows, verified profiles, physics gates, sensitivity checks, and scientifically honest animation semantics.

Adding a new Skill should keep the complete skill directory together with SKILL.md, metadata.json when available, upstream attribution, references, assets, and workflow scripts.

Installation

1. Clone the repository

powershell
git clone https://github.com/Cai-aa/CAE-Agent-Hub.git
Set-Location .\CAE-Agent-Hub

If you cloned the repository before the rename, the old text-to-cae remote may still work through GitHub redirects. Updating the remote URL is clearer:

powershell
git remote set-url origin https://github.com/Cai-aa/CAE-Agent-Hub.git

2. Use an MCP server

Each MCP folder has its own README and environment template. The common local pattern is:

powershell
Set-Location ".\MCP\<vendor>\<server folder>"
py -m venv .venv
.\.venv\Scripts\python.exe -m pip install -U pip
.\.venv\Scripts\python.exe -m pip install -e .

Then register the server with your MCP-capable client using the example configuration provided by that MCP.

Installing an MCP server does not install the underlying commercial CAE software or provide a solver license. The required CAE application, executable, license, bridge, and local environment must be available separately where applicable.

3. Use Skills

Skills are instruction modules, not solver binaries. Copy the complete skill directory into your agent's skill directory or attach the relevant SKILL.md as project context.

For Codex:

powershell
New-Item -ItemType Directory -Force -Path "$env:USERPROFILE\.codex\skills" | Out-Null
Copy-Item -Recurse -Force ".\Skill\abaqus\analysis\abaqus-static-analysis" "$env:USERPROFILE\.codex\skills\abaqus-static-analysis"

Example prompt:

text
Use the abaqus-static-analysis, abaqus-mesh, abaqus-job, and abaqus-odb skills.
Build a complete Abaqus static-analysis workflow, run it if the Abaqus MCP
or local Abaqus CLI is available, and report the exact files and commands used.

Text to CAE Viewer

The original viewer remains the browser-based result-inspection layer. It can display cases containing result_mesh.json even when the original solver is not installed.

powershell
Set-Location .\viewer
npm.cmd install
npm.cmd run dev

Open the Vite URL, usually:

text
http://127.0.0.1:4178/

Example cases:

text
http://127.0.0.1:4178/?case=cantilever
http://127.0.0.1:4178/?case=hole-plate
http://127.0.0.1:4178/?case=hole-plate-modal
http://127.0.0.1:4178/?case=sphere-impact
http://127.0.0.1:4178/?case=milling-3d
http://127.0.0.1:4178/?case=gear-mesh
http://127.0.0.1:4178/?case=bullet-plate

Repository Layout

text
CAE-Agent-Hub/
├── .github/
│   └── workflows/
├── MCP/
│   ├── Abaqus/
│   ├── CalculiX/
│   ├── HyperWorks/
│   ├── LAMMPS/
│   ├── OVITO/
│   ├── FEP-Agent-Hub/
│   └── Ansys/
│       ├── AEDT MCP/
│       ├── Fluent MCP/
│       └── Workbench MCP/
├── Skill/
├── Subagent/
├── assets/
├── models/
├── viewer/
├── .gitignore
├── LICENSE
├── README.md
└── README.zh-CN.md

The repository root currently contains the MCP, Skill, Subagent, assets, models, viewer, workflow, licensing, and bilingual documentation areas shown above. Individual MCP and Skill directories contain their own implementation and documentation structures.

Source Control Policy

The repository should include reusable source, documentation, tests, examples, templates, and skill instructions.

It should not include:

  • CAE software binaries or licenses.
  • Private machine paths or credentials.
  • Virtual environments and package caches.
  • Generated solver outputs such as ODB, case/data, AEDT results, Workbench projects, logs, and screenshots.
  • Large local result artifacts that can be regenerated.

Build

Build the frontend viewer:

powershell
Set-Location .\viewer
npm.cmd run build

Roadmap

The hub is designed to grow toward more mainstream simulation ecosystems:

  • More solver-specific MCP servers.
  • More productized Skill packs for repeatable modeling and validation workflows.
  • Shared result export formats for viewer and report generation.
  • Safer install prompts and verification scripts for each CAE application.

Contributing a New MCP or Skill

When extending the hub:

  1. Keep reusable source code and workflow instructions together.
  2. Provide examples and tests where appropriate.
  3. Provide a README for the new component.
  4. Keep private paths, credentials, licenses, virtual environments, and generated solver results out of source control.
  5. Follow the existing repository structure and naming conventions.
  6. For Skills, preserve the complete SKILL.md-based workflow and supporting references/assets.

License

This repository is released under the MIT License. See LICENSE for details.

Use CalculiX MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once CalculiX MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add CalculiX MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the CalculiX MCP MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "calculix": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the CalculiX MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the CalculiX MCP MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use CalculiX MCP to help me with this task?
CalculiX MCP
Sure. I read it.
Here is what I found using CalculiX MCP.

Frequently asked questions

What is the CalculiX MCP MCP server used for?

CalculiX MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use CalculiX MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use CalculiX MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use CalculiX MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With CalculiX MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect CalculiX MCP MCP to TypingMind?

CalculiX MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does CalculiX MCP MCP provide in TypingMind?

CalculiX MCP exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use CalculiX MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If CalculiX MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

Related MCP Servers

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇