Use Codex, Claude Code, or another AI agent to work with COMSOL Multiphysics models from the workflow you already use.
sim-plugin-comsol gives an agent practical COMSOL control paths: inspect
saved .mph files, search local COMSOL documentation, run saved models through
comsolbatch, compile settled Java recipes with comsolcompile, build or
modify models through the COMSOL Java API, and work through a shared visible
COMSOL Desktop session when the engineer wants to watch or intervene.
COMSOL itself and its mph Python binding are not bundled. See
LICENSE-NOTICE.md.
- Load and modify existing COMSOL
.mphmodels. - Search installed COMSOL help for module, API, and example-model details.
- Run saved models directly with COMSOL's own batch executable.
- Compile and run settled Java build-solve-extract recipes.
- Build and solve a model step by step while you watch the Model Builder.
- Inspect a saved
.mphfile before deciding what to change. - Run bounded edits, checks, plots, and result-export steps through COMSOL's Java API.
- Keep a structured audit trail of commands, health checks, and generated artifacts so results can be reviewed rather than guessed.
This repository is intended to be the complete COMSOL agent bundle: driver and bundled COMSOL skill. A receiving agent should not need a separate COMSOL skill checkout.
When the user only needs to know what is in a saved COMSOL model, use the
bundled offline inspection helpers before launching a heavyweight COMSOL
session. This is the right first step for questions like: "what physics,
parameters, studies, meshes, and result nodes are in this .mph?"
Use COMSOL's own executable when the task is a deterministic saved-model run or
fan-out over many .mph files:
& "C:\Program Files\COMSOL\COMSOL64\Multiphysics\bin\win64\comsolbatch.exe" `
-inputfile in.mph `
-outputfile out.mph `
-batchlog log.txtUse this when the workflow is a known-good Java recipe that should run in a
fresh COMSOL process and emit KPIs, exported data, or an output .mph.
Use a server-backed Java API session when the agent should build, inspect, solve, and debug a model across multiple steps. Use shared Desktop when the engineer wants to watch a live COMSOL Desktop client:
uv run sim connect --solver comsol --ui-mode gui --driver-option visual_mode=shared-desktop
uv run sim inspect session.health
uv run sim exec --file step.pyshared-desktop starts comsolmphserver, attaches a full COMSOL Desktop
client to that server, and binds agent snippets to the Desktop active model
tag. session.health should report model_builder_live: true and a
live_model_binding.ok value of true before relying on the GUI as a live
view of agent edits.
For agent projects, install sim-cli-core and the COMSOL plugin in the project environment:
uv init # only if this is not already a uv project
uv add sim-cli-core sim-plugin-comsol
uv run sim plugin sync-skills --target .agents/skills --copy
uv run sim check comsol
uv run sim plugin doctor comsol --deepFor Claude Code, sync the bundled skill to .claude/skills instead:
uv run sim plugin sync-skills --target .claude/skills --copyuv run sim ... runs sim from this project environment, so it sees this
project's plugins. Without uv, create and activate a venv, then install
sim-cli-core plus this plugin with python -m pip.
Give Codex, Claude Code, or another coding agent this instruction when the task is about COMSOL:
Use the bundled COMSOL skill from sim-plugin-comsol. First identify the real
COMSOL control path for the task: saved .mph inspection, local COMSOL docs,
direct comsolbatch saved-model execution, comsolcompile + comsolbatch for a
settled Java recipe, a server-backed Java API session, or the sim runtime /
shared Desktop when structured inspect/exec/checkpoint tools are useful. For
visible co-editing, use `sim connect --solver comsol --ui-mode gui
--driver-option visual_mode=shared-desktop` and verify
`session.health.live_model_binding.ok`. For non-trivial live modeling, establish
the target model identity and working folder early: load the given .mph, or set
a descriptive model tag/title and save an initial checkpoint .mph under a case
workdir.
The bundled skill entry point is:
src/sim_plugin_comsol/_skills/comsol/SKILL.md
sim-plugin-comsol is a Python package that extends
sim-cli. sim-cli provides a common
agent runtime surface (connect, exec, inspect, screenshot, run) for
the paths that benefit from a managed live session. This plugin supplies the
COMSOL-specific driver, bundled COMSOL agent skill, local documentation helper,
and COMSOL-native workflow guidance.
The plugin registers three entry-point groups:
[project.entry-points."sim.drivers"]
comsol = "sim_plugin_comsol:ComsolDriver"
[project.entry-points."sim.skills"]
comsol = "sim_plugin_comsol:skills_dir"
[project.entry-points."sim.plugins"]
comsol = "sim_plugin_comsol:plugin_info"sim.drivers exposes the driver class; sim.skills exposes a directory of
skill files bundled inside the wheel; sim.plugins exposes plugin metadata for
discovery.
git clone https://github.com/svd-ai-lab/sim-plugin-comsol
cd sim-plugin-comsol
uv sync
uv run sim plugin list
uv run sim check comsol
uv run pytestApache-2.0. See LICENSE and LICENSE-NOTICE.md.