No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by yusong652 · MCP Server · ★ 103
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pfc-mcp safe to install? View the security audit →
pfc-mcp English | 简体中文 pfc-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. Tools (10) 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. First-time Setup Prerequisi
| Stars | 103 |
| Forks | 11 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.8067223386706/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-25 |
| Created | 2026-02-11 |
| Platforms | claude-code, cli, codex, gemini, mcp, python |
| Est. Tokens | ~14k |
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pfc-mcp is MCP server connecting AI agents to ITASCA PFC — run DEM simulations through natural conversation. It is categorized as a MCP Server with 103 GitHub stars.
pfc-mcp is primarily written in Python. It covers topics such as ai-agent, claude, claude-code.
You can find installation instructions and usage details in the pfc-mcp GitHub repository at github.com/yusong652/pfc-mcp. The project has 103 stars and 11 forks, indicating an active community.
pfc-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to pfc-mcp on Agent Skills Hub include claude-prompts, deterministic-agent-control-protocol, XActions. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: