Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Build, run, inspect, and verify finite-element simulations with AgentFEM.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
AGENTFEM_MCP_ROOTS, AGENTFEM_COMMAND你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"agentfem": {
"command": "uvx",
"args": [
"agentfem-mcp"
],
"env": {
"AGENTFEM_MCP_ROOTS": "your-value",
"AGENTFEM_COMMAND": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add agentfem --env AGENTFEM_MCP_ROOTS=your-value --env AGENTFEM_COMMAND=your-value -- uvx agentfem-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentfem": {
"command": "uvx",
"args": [
"agentfem-mcp"
],
"env": {
"AGENTFEM_MCP_ROOTS": "your-value",
"AGENTFEM_COMMAND": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"agentfem": {
"type": "stdio",
"command": "uvx",
"args": [
"agentfem-mcp"
],
"env": {
"AGENTFEM_MCP_ROOTS": "your-value",
"AGENTFEM_COMMAND": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
AGENTFEM_MCP_ROOTS envAGENTFEM_COMMAND env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 haoming-luo 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Spec Driven Development, Remote Desktop Commander, NexusWindows
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Windows computer use in the background: desktop apps driven without your mouse or keyboard.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
One finite-element platform. Any compatible agent. Evidence intact.
AgentFEM MCP gives Codex, Claude, and other MCP-compatible agents a small, stable tool surface for building and running inspectable finite-element projects. AgentFEM remains the deterministic scientific engine; the agent interprets intent and explains evidence.
Install from PyPI · Discover in the official MCP Registry · Read the AgentFEM agent guide
Already using an AI assistant in the terminal? You can use AgentFEM directly through its CLI. Choose between CLI, MCP, and skills →
For a supported desktop client on macOS or Linux, download the tiny AgentFEM-0.1.0.mcpb connection bundle from the 0.1.0 release. It installs only the interface; the AgentFEM scientific runtime remains the single source of solver capabilities, upgrades, and results.
It exposes seven tools—not hundreds of solver internals:
| Tool | Purpose |
|---|---|
describe_system | Inspect the installed runtime and a compact capability map |
create_project | Start from a version-matched AgentFEM template |
validate_project | Report process success and scientific acceptance separately |
inspect_project | Read project and recent-run identity |
submit_run | Launch an isolated serial or MPI process |
get_run_status | Observe a durable background job |
get_result_summary | Read a compact result and trust state; request full evidence only when needed |
Want to see the underlying workflow before installing?
AgentFEM must already be installed. With uvx, Codex needs one command and the adapter remains isolated from the numerical environment:
codex mcp add agentfem \
--env AGENTFEM_MCP_ROOTS=/absolute/path/to/AgentFEMProjects \ -- uvx --from agentfem-mcp agentfem-mcp
Or install the lightweight adapter in the active environment:
python -m pip install agentfem-mcp
The 0.1.0 lifecycle is acceptance-tested with the public AgentFEM 0.3.3 CLI contracts and the current 0.3.7 development line.
Give your agent a project root, not your whole home directory.
Codex officially supports local stdio MCP servers. Confirm the connection with codex mcp list, then begin with:
Use AgentFEM to create, validate, run, verify, and briefly explain a 2D
cantilever. Keep the project and result paths visible.
On macOS or Linux, open the release's .mcpb file in a supporting desktop client and choose the one project folder the connection may access. AgentFEM must already be installed. Windows support currently uses the explicit WSL2 configuration from the AgentFEM guide rather than claiming a native bridge.
Claude Code:
claude mcp add agentfem --scope user \
--env AGENTFEM_MCP_ROOTS=/absolute/path/to/AgentFEMProjects \ -- uvx --from agentfem-mcp agentfem-mcp
Claude Desktop configuration:
{
"mcpServers": { "agentfem": { "command": "agentfem-mcp", "env": { "AGENTFEM_MCP_ROOTS": "/absolute/path/to/AgentFEMProjects" } } } }
If a desktop app cannot see the activated conda environment, set AGENTFEM_COMMAND to the absolute agentfem executable. The official macOS runtime, AgentFEM WSL2 runtime, and common agentfem-env/fenicsx-env layouts are also detected automatically.
VS Code can place the same local server in .vscode/mcp.json:
{
"servers": { "agentfem": { "type": "stdio", "command": "uvx", "args": ["--from", "agentfem-mcp", "agentfem-mcp"], "env": { "AGENTFEM_MCP_ROOTS": "${workspaceFolder}" } } } }
The server is model-neutral. A DeepSeek or other model can use it through any host that implements local MCP tools. ChatGPT connectors require a public HTTPS server; AgentFEM will add that route only with a real authenticated compute and artifact boundary, rather than silently uploading local models through this adapter.
The repository's minimal, unprivileged Dockerfile exists for MCP directory startup and tool-introspection checks. It intentionally contains the public MCP adapter, not a second AgentFEM solver distribution. Real simulations should use the installed AgentFEM runtime and an explicit local project root.
This repository contains a portable AgentFEM workflow skill and a local Codex marketplace under .agents/plugins/. It combines scientific operating guidance with the same MCP server; it does not create a second solver interface.
AI agent
│ seven typed MCP tools ▼ AgentFEM MCP ── process + path boundary │ versioned JSON contracts ▼ AgentFEM CLI → Study → Model → Step → SimulationResult ▼ FEniCSx / PETSc / MPI
completed, verified, and validated remain different scientific states.| Variable | Meaning |
|---|---|
AGENTFEM_MCP_ROOTS | Approved project roots separated by the platform path separator |
AGENTFEM_COMMAND | Absolute path to a specific agentfem executable |
With no root configured, the server restricts access to its working directory. The default maximum is 16 MPI ranks and can only be changed by the server operator, not by an agent tool call.
python -m pip install -e '.[test]'
ruff check . pytest python -m build
See SECURITY.md for the trust boundary and CONTRIBUTING.md for contribution expectations. The first release evidence records protocol, package, and real-solver acceptance separately.
AgentFEM MCP is Apache-2.0 licensed and maintained as an official companion to AgentFEM.