PromptMC
MCP serverCommunity
Puts a schema-checking gate between an AI assistant and OpenMC, then runs, plots and parses validated decks over MCP. By rjonace.
2 starsUpdated 5 months agoGitHub data from 5 Nov 2026
At a glance
- Type
- MCP server
- Works with
- OpenMC
- How it connects
- Drives a running copy of the tool
- Access
- Can modify models
- Tool versions
- PromptMC 0.3.5 (alpha); works against an installed OpenMC and its cross_sections.xml
- Operating systems
- macOS, Linux
- Needs a OpenMC licence
- No
- Transport
- Local (stdio)
- AI clients documented
- Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Google Antigravity
- Licence
- MIT
- Language
- Python
What it can do
- Validates settings, geometry and materials XML against typed schemas and returns structured errors an assistant can correct, without needing OpenMC installed.
- Turns a plain-English request into a deck from templates such as a PWR pin cell or Godiva, using a keyword planner that calls no language model.
- With OpenMC installed, runs simulations, performs geometry-debug overlap checks and returns 2D slice plots into the chat.
- Parses k-effective and tallies from statepoint files without you touching HDF5.
Limitations
- Alpha software; validation covers PromptMC's supported schemas, not every OpenMC feature.
- Running, plotting and geometry checks need OpenMC and cross-section data set through OPENMC_CROSS_SECTIONS.
- The author states the goal is faster OpenMC iteration, not autonomous reactor design.
Install
pip install promptmc # core: CLI, schema validation, local planner, MCP serverclaude mcp add promptmc --scope user -- promptmc-mcp{
"mcpServers": {
"promptmc": {
"command": "promptmc-mcp",
"env": {
"OPENMC_CROSS_SECTIONS": "/path/to/cross_sections.xml"
}
}
}
}MCP servers and skills run code on your computer. Review the source before installing.
AI-generated models, drawings and results must be checked by a qualified engineer before use.