Kratos-MCP-Server

# Kratos MCP Server [](https://github.com/loumalouomega/Kratos-MCP-Server/actions/workflows/ci.yml) [](https://loumalouomega.github.io/Kratos-MCP-Server/) [](https://github.com/loumalouomega/Kratos-MCP-Server/releases) [](https://pypi.org/project/kratos-mcp-server/) [](https://www.python.org/) [](LICENSE) An [MCP](https://modelcontextprotocol.io) server that lets AI assistants drive [Kratos Multiphysics](https://github.com/KratosMultiphysics/Kratos) finite element simulations end to end: - **Introspect** the installation: applications, elements, conditions, constitutive laws, variables, solvers and their default parameters. - **Scaffold** simulation cases from templates: structural (static/dynamic/modal), thermal (transient/stationary) and fluid (transient incompressible) — ProjectParameters.json, Materials.json and structured MDPA meshes with named boundary regions. - **Run** simulations as managed background jobs (status, live logs, progress, cancel) that survive server restarts. - **Post-process** VTK results: summaries, point probes, convergence analysis. - **Preview** results without ParaView: PNG screenshots and GIF animations (deformed shapes, field contours) rendered with pyvista and shown inline in the conversation — optional `viz` extra. 33 tools, 7 resources and 4 guided prompts. See the full documentation in [`docs/`](docs/) (VitePress). ## Quick start A local Kratos build is **not required** — the server can pip-install Kratos itself on first use. **Once published to PyPI**, no clone needed — `uvx` fetches and runs it: ```bash claude mcp add kratos -- uvx kratos-mcp-server ``` **From a local checkout** (current state, before the first PyPI release): ```bash git clone https://github.com/loumalouomega/Kratos-MCP-Server cd Kratos-MCP-Server uv sync claude mcp add kratos -- uv --directory "$PWD" run kratos-mcp ``` Then ask your assistant something like: > Check the Kratos installation — install it if it's missing — then set up > a cantilever plate 1 m × 0.2 m fixed on the left with a 1 MN/m downward > load on the right edge, run it, and report the tip deflection. The assistant calls `kratos_install` the first time and reuses it afterwards. If you already have a compiled Kratos checkout, skip that and point `KRATOS_ROOT` at it instead (`-e KRATOS_ROOT=/path/to/Kratos` on the `claude mcp add` line) — see [Installation](docs/guide/installation.md). ## Requirements - Python ≥ 3.10, [uv](https://docs.astral.sh/uv/) - Kratos Multiphysics, either pip-installed via `kratos_install` (Linux/Windows x86_64 only — no macOS wheels) or a compiled build (tested with 10.4, StructuralMechanics / ConvectionDiffusion / FluidDynamics / LinearSolvers applications) - Optional, for `results_render`/`results_animate`: the `viz` extra (`uv sync --extra viz` or `pip install 'kratos-mcp-server[viz]'`) and a working OpenGL context (on headless machines: Xvfb or OSMesa VTK wheels — see [docs/tools/visualization.md](docs/tools/visualization.md)) ## Architecture in one paragraph Kratos is never imported in the server process — it prints a banner on import (which would corrupt the stdio JSON-RPC stream) and can abort the process on solver errors. Short operations run in a **worker** subprocess that returns JSON through a result file; simulations run **detached** with per-job directories under `~/.kratos-mcp/jobs/`. See [docs/guide/architecture.md](docs/guide/architecture.md). ## Development ```bash uv run pytest -m "not kratos" # unit tests (no Kratos needed) uv run pytest -m kratos # integration tests against the real build npm install && npm run docs:dev # documentation site ``` ## License [MIT](LICENSE)