Getting started with FERS

FERS is a finite-element solver for beams, frames and trusses with EN 1993-1-1 steel checks. The same Rust engine runs in your browser, in a Python script, in a Node process and behind the REST API — so you can start with no install at all and move to code whenever it pays off.

What is FERS?

FERS pairs a Rust solver with a Python modelling layer and a browser workspace. You decide where each step runs:

  • Local only — install the package (pip install FERS, imported as fers_core), define the problem in Python, solve on your machine, export structured results. No account, no network.
  • Browser only — build the model in the web workspace and solve it client-side in WebAssembly. Nothing is uploaded, and no account is needed to get an answer.
  • Hybrid — prototype in a script, then push the model to FERS Cloud for visualization, sharing and 3D export; or build it in the browser and export the JSON into a script.

All four routes consume the same model JSON, in SI base units, so a model started one way can always be finished another.

Documentation

Each page below is a complete, self-contained topic.

Pick your route

Same engine, same results, four ways in.

Python

Build models as objects, sweep parameters in a loop, and get results back as data. The route for anything repetitive or that needs to live in version control.

Structural analysis in Python

JavaScript

A WebAssembly build of the solver, published on npm. Runs in the browser or Node with no server round-trip, so the model never leaves the user's machine.

Structural analysis in JavaScript

REST API

Plain HTTP from any language, with an OpenAPI 3.1 spec you can import straight into a client generator or a ChatGPT Custom GPT Action.

REST API reference

For AI agents

FERS has a remote MCP server, so Claude, ChatGPT, Cursor and VS Code can build and solve structural models directly — including EN 1993-1-1 member checks with a per-clause trace. Connect it once and your assistant calculates rather than guesses.

Agents that would rather read than call: llms.txt indexes this site, llms-full.txt is the whole documentation in one fetch, and every page here has a plain-markdown twin at /docs/<topic>.md.

Set up the MCP server

Getting help

Resources for troubleshooting and support.

Examples

Runnable scripts on GitHub for understanding the FERS syntax.

View examples

Submit a ticket

Have an account? Submit a support ticket and track its progress.

Open a ticket

GitHub repository

Examples, issues and feature requests.

View on GitHub

Email the team

Get help from our support team.

Contact support

Frequently asked questions

Do I need to install anything to try FERS?

No. The browser workspace and every calculator solve client-side in WebAssembly, with no account and no install. Installing the Python or npm package is only worth it once you want to script something.

What does the free tier include?

Solving models up to 100 members, in the browser or locally, with no account. Pro raises that to 10,000 members and adds cloud model storage, at €19.95/month. The API and agent channels get 100 free solves per rolling week.

Is my model uploaded to your servers?

Not unless you ask. Browser and local solves run entirely on your machine. Only the REST and MCP endpoints send a model to FERS Cloud, and cloud storage is opt-in.

How accurate is it?

Results are validated against closed-form solutions and the standard NAFEMS finite-element benchmarks, both published with the target-versus-FERS error — see accuracy benchmarks and NAFEMS. Verify a case you know before trusting one you do not.

Which units and axis conventions does FERS use?

SI base units in the model JSON — metres, newtons, pascals — with angles in degrees. The strong bending axis is the local z axis, so i_z governs ordinary bending. Full details on conventions and units.

Can an AI assistant use FERS directly?

Yes. The MCP server exposes the solver, the model builders and the Eurocode checks as tools that Claude, ChatGPT, Cursor and VS Code can call.