# ITASCA PFC

> Use this tool when you need to simulate complex particle flows and interactions, solving problems in fields like engineering, physics, and materials science. It provides a comprehensive interface for executing and monitoring discrete element simulations, with inputs including scripts and simulation parameters, and outputs such as plot images and task status. Ideal for use in research, development, and analysis contexts where precise modeling of particle behavior is required.

Canonical page: https://skillsregistry.net/skills/gh-yusong652-itasca-pfc  
JSON: https://api.skillsregistry.net/v1/skills/gh-yusong652-itasca-pfc

## Description

Provides full access to ITASCA PFC (Particle Flow Code) discrete element simulation software. Includes 5 documentation tools for browsing and searching the PFC command tree, Python SDK reference, and contact model docs, plus 5 execution tools for submitting scripts, monitoring tasks, interrupting simulations, and capturing plot images. Requires PFC 7.0 and a WebSocket bridge running inside the PFC process.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/gh-yusong652-itasca-pfc)
- **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": "gh-yusong652-itasca-pfc"
    }
  }
}
```

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