# PFC - ITASCA Discrete Element Simulation

> Use this tool when you need to simulate complex systems with discrete elements, such as granular materials or particle interactions, to analyze and visualize their behavior. It solves problems related to material failure, deformation, and flow, providing valuable insights for engineering and scientific applications. The tool takes in simulation parameters and material properties as inputs and outputs detailed plots, graphs, and data for further analysis.

Canonical page: https://skillsregistry.net/skills/io-github-yusong652-pfc  
JSON: https://api.skillsregistry.net/v1/skills/io-github-yusong652-pfc

## Description

Give AI agents full access to ITASCA PFC - documentation, simulation, and plot capture.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.2.5
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-17

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.yusong652%2Fpfc)
- **Repository:** <https://github.com/yusong652/pfc-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "io-github-yusong652-pfc"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-yusong652-pfc` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-yusong652-pfc/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt