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pfc-mcp
Advanced tools
pfc3d>model new ;now, with LLM.
itasca-mcp connects AI agents to ITASCA PFC — Itasca's discrete element method (DEM) code — through the Model Context Protocol. Browse documentation, run simulations, and execute code, all through natural conversation.
pfc3d>model solve ;LLM solves.

5 documentation tools — browse and search PFC commands, Python API, and reference docs. No bridge required.
5 execution tools — interactive REPL, task submission, progress monitoring, interruption, and history. Requires bridge.
uvx)Copy this to your AI agent and let it self-configure:
Fetch and follow this bootstrap guide end-to-end:
https://raw.githubusercontent.com/yusong652/itasca-mcp/main/docs/agentic/itasca-mcp-bootstrap.md
1. Register the MCP server in your client config:
{
"mcpServers": {
"itasca-mcp": {
"command": "uvx",
"args": ["itasca-mcp"]
}
}
}
2. Start the bridge from inside PFC:
Download addon.py, then use either of these two flows inside PFC:
Restart your AI agent (Claude Code, Codex CLI, Gemini CLI, etc.) and ask it to call itasca_execute_code to verify the connection.
Once first-time setup is done, each new PFC session only needs the bridge re-started — run this in PFC's IPython console and you're back online:
import itasca_mcp_bridge
itasca_mcp_bridge.start()
start() checks PyPI for a newer bridge release and self-upgrades before starting. The MCP client config persists.
version parameterSee Troubleshooting in the bootstrap guide.
See Developer Guide: Install and Run from Source.
PRs and issues are welcome! See the Developer Guide to get started.
MIT - see LICENSE.
FAQs
DEPRECATED - use itasca-mcp. MCP server for ITASCA PFC simulation workflows
The pypi package pfc-mcp receives a total of 38 weekly downloads. As such, pfc-mcp popularity was classified as not popular.
We found that pfc-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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