PFC - ITASCA Discrete Element Simulation
平台与服务by yusong652
让 AI agents 完整访问 ITASCA PFC,包括文档查询、仿真操作以及绘图结果捕获。
什么是 PFC - ITASCA Discrete Element Simulation?
让 AI agents 完整访问 ITASCA PFC,包括文档查询、仿真操作以及绘图结果捕获。
README
pfc-mcp
pfc3d>model new ;now, with LLM.
pfc-mcp connects AI agents to ITASCA PFC through the Model Context Protocol — browse documentation, run simulations, and execute code, all through natural conversation.
pfc3d>model solve ;LLM solves.

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.
Quick Start
Prerequisites
- ITASCA PFC 6.0, 7.0, or 9.0 installed
- uv installed (for
uvx)
Agentic Setup (Recommended)
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/pfc-mcp/main/docs/agentic/pfc-mcp-bootstrap.md
Manual Setup
1. Register the MCP server in your client config:
{
"mcpServers": {
"pfc-mcp": {
"command": "uvx",
"args": ["pfc-mcp"]
}
}
}
2. Start the bridge from inside PFC:
Download addon.py, then use either of these two flows inside PFC:
- Copy the file contents into the PFC IPython console and run them
- Or download the file and execute it in PFC GUI
Verify
Restart your AI agent (Claude Code, Codex CLI, Gemini CLI, etc.) and ask it to call pfc_execute_code to verify the connection.
Features
- Multi-version PFC support - command docs for PFC 6.0, 7.0, and 9.0 via the
versionparameter - Hierarchical documentation browsing - agents navigate the PFC command tree to discover capabilities and boundaries, reducing hallucinated commands
- Enhanced plot documentation - plot items reference docs supplementing the official documentation
- Interactive REPL - rapid iteration before committing to full scripts; agents can quickly test and refine code
- Task lifecycle management - submit long-running simulations, monitor progress, interrupt running tasks, and browse task history
- Multi-client compatible - works with Claude Code, Codex CLI, Gemini CLI, OpenCode, toyoura-nagisa, and other MCP clients
Troubleshooting
Development
See Developer Guide: Install and Run from Source.
<a href="https://glama.ai/mcp/servers/yusong652/pfc-mcp"> <img width="200" height="105" src="https://glama.ai/mcp/servers/yusong652/pfc-mcp/badge" alt="pfc-mcp MCP server" /> </a>Contributing
PRs and issues are welcome! See the Developer Guide to get started.
License
MIT - see LICENSE.
<!-- mcp-name: io.github.yusong652/pfc -->常见问题
PFC - ITASCA Discrete Element Simulation 是什么?
让 AI agents 完整访问 ITASCA PFC,包括文档查询、仿真操作以及绘图结果捕获。
相关 Skills
MCP构建
by anthropics
聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。
✎ 想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。
Slack动图
by anthropics
面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。
✎ 帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。
MCP服务构建器
by alirezarezvani
从 OpenAPI 一键生成 Python/TypeScript MCP server 脚手架,并校验 tool schema、命名规范与版本兼容性,适合把现有 REST API 快速发布成可生产演进的 MCP 服务。
✎ 帮你快速搭建 MCP 服务与后端 API,脚手架完善、扩展顺手,尤其适合想高效验证服务能力的开发者。
相关 MCP Server
Slack 消息
编辑精选by Anthropic
Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。
✎ 这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。
by netdata
io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。
✎ 这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。
by d4vinci
Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。
✎ 这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。