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AgentFEM

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View Repository

Build, run, inspect, and verify finite-element simulations with AgentFEM.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON â–¾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for AgentFEM, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives💻 More in Developer Tools

Documentation Overview

AgentFEM

AgentFEM MCP

CI PyPI MCP Registry AgentFEM MCP server

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

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:

ToolPurpose
describe_systemInspect the installed runtime and a compact capability map
create_projectStart from a version-matched AgentFEM template
validate_projectReport process success and scientific acceptance separately
inspect_projectRead project and recent-run identity
submit_runLaunch an isolated serial or MPI process
get_run_statusObserve a durable background job
get_result_summaryRead a compact result and trust state; request full evidence only when needed

Bring it to life

Want to see the underlying workflow before installing?

  • Explore a 3D structural-design case: compare support weight and deflection under the same load. The public browser edition uses precomputed candidates.
  • Try the simulation-to-surrogate mini-lab: ten real FEM outputs, a small NumPy model, and an interactive notebook.
  • Follow the AI-assisted cantilever quick start: create a readable project, run it, and inspect its numerical result.

AgentFEM must already be installed. With uvx, Codex needs one command and the adapter remains isolated from the numerical environment:

bash
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:

bash
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

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.

Claude Desktop and compatible clients

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:

Terminal
claude mcp add agentfem --scope user \
  --env AGENTFEM_MCP_ROOTS=/absolute/path/to/AgentFEMProjects \
  -- uvx --from agentfem-mcp agentfem-mcp

Claude Desktop configuration:

config.json
{
  "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 and other models

VS Code can place the same local server in .vscode/mcp.json:

config.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.

Directory health image

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.

Local Codex plugin

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.

The contract

text
AI agent
   │  seven typed MCP tools
   â–¼
AgentFEM MCP ── process + path boundary
   │  versioned JSON contracts
   â–¼
AgentFEM CLI → Study → Model → Step → SimulationResult
   â–¼
FEniCSx / PETSc / MPI
  • No language model or API key is embedded in AgentFEM MCP.
  • No shell command or arbitrary Python string is accepted from a tool call.
  • All project paths must remain under explicitly approved roots.
  • Numerical runs occur in child processes, isolating PETSc/MPI lifetime from the MCP server.
  • completed, verified, and validated remain different scientific states.
  • Compact system discovery preserves AgentFEM's website, repository, citation, and its consent-first, once-per-release-series community invitation. The MCP server never performs an account action for the user.

Environment controls

VariableMeaning
AGENTFEM_MCP_ROOTSApproved project roots separated by the platform path separator
AGENTFEM_COMMANDAbsolute 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.

Development

bash
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.

Read the full README →View source on GitHub →

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Reviews

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Frequently Asked Questions about AgentFEM

We don't have a confirmed install command for AgentFEM yet, so we don't publish a generated one — a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/haoming-luo/agentfem-mcp) for the current steps.

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Technical Specs & Signals

Category💻Developer Tools
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Last updatedSep 28, 2026
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27Quality signal: Emerging · 27/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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