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Ansys CFX

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An MCP server that enables AI assistants to interact with Ansys CFX through PyCFX, supporting natural-language-assisted CFX-Pre, CFX Solver, and CFD-Post workfl

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Описание

An MCP server that enables AI assistants to interact with Ansys CFX through PyCFX, supporting natural-language-assisted CFX-Pre, CFX Solver, and CFD-Post workflows for setup, execution, and postprocessing.

README

PyAnsys Python Apache

Ansys CFX-MCP (ansys-cfx-mcp) is a Model Context Protocol (MCP) server that enables AI assistants to interact with Ansys CFX through PyCFX. It enables natural-language-assisted CFX-Pre, CFX Solver, and CFD-Post workflows for setup, execution, and postprocessing.

It is built on PyAnsys Common MCP (ansys-common-mcp), the shared PyAnsys MCP foundation.

This package is self-contained and works as a standalone server for any MCP host. It exposes a compact CFX-oriented tool surface so you can connect to CFX sessions, inspect bounded model context, generate small PyCFX snippets, validate code, and coordinate common solver and CFD-Post actions.

For quick-start, configuration, architecture, examples, and per-tool reference material, see the PyCFX-MCP documentation.

Overview

Ansys CFX-MCP is a stateless MCP leaf. Your LLM host, such as Visual Studio Code Copilot, Claude Desktop, Cursor, or a custom agent, calls a focused set of tools to drive live CFX-Pre, CFD-Post, and CFX Solver sessions. Custom Python runs through a validated, Python-level restricted execution path. This is not an operating-system or container sandbox.

Key features:

  • CFX session management: Start or attach to CFX-Pre, CFX Solver, and CFD-Post workflows.
  • Workflow routing: Use one compact cfx_workflow tool for common CFX lifecycle actions.
  • Bounded model context: Inspect summaries, named objects, API help, allowed values, and selected state snippets without dumping entire models into an MCP client.
  • Deterministic-first codegen: Generate PyCFX-oriented snippets from bundled CFX recipes first, with an optional server-side LLM fallback only for unmatched codegen prompts.
  • Validated execution: Run custom snippets in a persistent PyCFX execution context with strict AST validation, guarded imports, and limited built-in functions.
  • Flexible MCP transport: Run over STDIO for local clients or Streamable HTTP for trusted local integrations.

Tool surface

The default MCP surface includes nine tools:

Group Tools
Connection and session connect, disconnect, and session_status
CFX workflow routing cfx_workflow
Bounded model context cfx_model_context
Code generation and execution codegen, clarify, run_code, and validate_code

The server also exposes a toolsets://definition MCP resource for clients or conductors that group related tools. The default CFX toolsets cover connection management, CFX workflow routing, CFX model context, code generation, and code execution.

Requirements

Requirement When needed Notes
Python 3.12 or later Always 3.12, 3.13 and 3.14 are supported
Core runtime dependencies Always (installed automatically) ansys-common-mcp, fastmcp, pydantic, and requests
A licensed local Ansys CFX installation To launch or attach CFX tools Required for workflows that use CFX-Pre, CFX Solver, or CFD-Post
Optional LLM fallback Only for unmatched codegen prompts Native providers through the LiteLLM SDK with ansys-cfx-mcp[providers], or any OpenAI-compatible chat completions endpoint such as a LiteLLM proxy

PyCFX and Ansys CFX are required for live-session tools. Any tool that touches a CFX app (connect, run_code, cfx_workflow, cfx_model_context, and session_status) requires ansys-cfx-core and a licensed CFX installation on your machine.

Installation

Install the latest release for users:

pip install ansys-cfx-mcp

Install the latest release for developers:

git clone https://github.com/ansys/pycfx-mcp.git
cd pycfx-mcp
pip install -e ".[dev,doc]"

Usage

Run PyCFX-MCP over STDIO, the default transport for desktop MCP clients:

ansys-cfx-mcp --transport stdio

Or, run PyCFX-MCP over Streamable HTTP:

ansys-cfx-mcp --transport http --host 127.0.0.1 --port 8000

Use STDIO for desktop MCP clients that launch the server process. Use Streamable HTTP only on trusted networks or behind infrastructure that provides authentication and TLS.

Starting PyCFX-MCP only makes the tools available. You still need an MCP-compatible client, such as Visual Studio Code Copilot, Claude Desktop, Cursor, or another assistant host, to connect to PyCFX-MCP. For more information, see IDE and client configuration in the PyCFX-MCP documentation.

Configuration

The default server needs no LLM configuration. The codegen path first applies guardrails and deterministic CFX recipes. If no recipe matches, only the codegen tool can fall through to the optional server-side LLM fallback. The cfx_workflow, cfx_model_context, validate_code, and run_code tools do not call an LLM.

To enable the optional model- and provider-agnostic LLM fallback or tune TLS and transport settings, see Configuration in the PyCFX-MCP documentation.

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.

Resources

For general PyAnsys questions, email [email protected].

from github.com/ansys/pycfx-mcp

Установить Ansys CFX в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install ansys-cfx-mcp

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add ansys-cfx-mcp -- uvx ansys-cfx-mcp

Пошаговые гайды: как установить Ansys CFX

FAQ

Ansys CFX MCP бесплатный?

Да, Ansys CFX MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Ansys CFX?

Нет, Ansys CFX работает без API-ключей и переменных окружения.

Ansys CFX — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Ansys CFX в Claude Desktop, Claude Code или Cursor?

Открой Ansys CFX на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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