PFC FAQs

Question 1

How does PFC-MCP manage long-running simulations?

Accepted Answer

It uses a robust task queue with live status updates, allowing AI agents to monitor output and status in real-time. It also supports callback-based control to gracefully interrupt simulations or capture plots mid-run.

Question 2

What is PFC-MCP?

Accepted Answer

PFC-MCP is an MCP server that provides AI agents full access to ITASCA PFC, enabling them to browse documentation, run simulations, and capture plots through natural conversation.

Question 3

What is the Model Context Protocol (MCP)?

Accepted Answer

The Model Context Protocol (MCP) is the framework PFC-MCP is built upon, allowing it to turn any MCP-compatible AI client into a powerful PFC co-pilot, facilitating interaction via AI agents.

Question 4

What are the main capabilities of PFC-MCP for AI agents?

Accepted Answer

AI agents can browse PFC command trees and documentation, execute Python scripts for simulations, manage running tasks across sessions, interrupt simulations, and capture plot images with custom configurations.

Question 5

Is ITASCA PFC required to use PFC-MCP?

Accepted Answer

While documentation browsing works standalone, full execution capabilities (running simulations, managing tasks, capturing plots) require a running ITASCA PFC 7.0 instance with the `pfc-mcp-bridge` installed.

PFC

PFC

主要功能

使用案例

主要功能

使用案例