How do I install the cloudHPC MCP server?

Install it with pipx or pip from the Git repository, using `pipx install git+https://github.com/CFD-FEA-SERVICE/cloudhpc-mcp` or the equivalent `pip install` command. Python 3.10 or newer, a cloudHPC account, and an API key are required.

How do I configure the cloudHPC MCP server with an API key?

Set the `CLOUDHPC_APIKEY` environment variable in the MCP client configuration. If it is not set, the server reads `~/.cfscloudhpc/apikey`. The key grants full account access and should be kept private.

Does cloudHPC work with Claude Desktop, Codex, Gemini CLI, and VS Code?

Yes, the README documents Claude Desktop, Claude Code, Codex CLI, Gemini CLI, and VS Code Copilot agent mode. Local clients run the `cloudhpc-mcp` stdio command, while web apps use the hosted endpoint where supported.

Can the cloudHPC MCP server access local simulation files?

Yes, when installed locally it can inspect case folders, upload folders, and download results to the computer. The hosted endpoint cannot read local files directly, so use temporary upload and download links instead.

CloudHPC

engineeringsimulationscloud-computingmcp

Run and manage cloudHPC engineering simulations from an MCP-compatible AI assistant.

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.

Add to Cursor Add to VS Code

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Remote HTTP

Configure Environment Variables (API Keys, Tokens, Options):

Add required secrets below — values are included directly in the generated snippet so you can copy and paste with confidence.

Quick Add:

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "cloudhpc": {
      "url": "https://mcp.cloudhpc.cloud/mcp",
      "env": {
        "CLOUDHPC_APIKEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

The cloudHPC MCP server connects AI assistants to cloudHPC for preparing, launching, monitoring, and retrieving engineering simulations. It supports cloudHPC solvers including FDS, OpenFOAM, CalculiX, SU2, EnergyPlus, and others, with resource recommendations and solver-specific guidance. A local installation can inspect case folders and save downloaded results, while the hosted endpoint uses upload and download links instead. Actions that incur charges or delete data require confirmation.

Use cases

Inspect a local FDS or OpenFOAM case

Recommend vCPU and RAM resources

Launch and monitor cloud simulations

Download completed simulation results

Start a remote desktop for post-processing

Key features

Solver-specific case guidance

vCPU and RAM recommendations

Simulation launch, monitoring, stopping, and resuming

Storage browsing and result downloads

Remote Linux or Windows desktops

Confirmation for billable and destructive actions

Capabilities & Tool Schemas (10)Self-reported

Inspect callable tools, capabilities, and parameters exposed to AI agents by CloudHPC.

suggest_resources

vCPU and RAM type recommendation, with reasoning

solver_guide

How to prepare a case for a solver: input files, what cloudHPC does automatically, restart, optional settings, parallelism, logs

launch_simulation

Launch a run (**asks for confirmation**)

sync_simulation

Upload partial results of a running job

stop_simulation

Soft or hard stop (**asks for confirmation**)

resume_simulation

Resume a stopped run with the same solver, vCPU, RAM type and folder (FDS and OpenFOAM; **asks for confirmation**)

How CloudHPC works

What cloudHPC does

The cloudHPC MCP server lets an MCP-compatible assistant work with engineering simulations hosted by cloudHPC. It can inspect a local case, identify supported solver data, estimate model size, recommend vCPU and RAM options, upload files, start a run, monitor its status, diagnose known errors, and retrieve result archives.

Supported solvers are those available on cloudHPC. The README specifically lists FDS, OpenFOAM, snappyHexMesh, DAFoam, code_aster, CalculiX, OpenRadioss, SU2, openTELEMAC, LIGGGHTS, OpenLB, EnergyPlus, and CONTAM. Use it when simulation setup, resource selection, run management, or result retrieval would benefit from conversational access.

How it works

The cloudHPC MCP server can run locally through the cloudhpc-mcp command or remotely at https://mcp.cloudhpc.cloud/mcp. The local mode can access case folders on the computer and provides tools for inspecting, uploading, and downloading local files. The hosted mode cannot read the computer directly; cases must be transferred with temporary upload and download links or through the cloudHPC web application.

Its tools cover case inspection, solver instructions, machine and solver listings, resource recommendations, simulation launch and status checks, partial-result synchronization, stopping and resuming runs, storage browsing, result downloads, remote desktop access, and API usage. A Linux or Windows remote desktop can be started for post-processing, but it remains billable until stopped.

Operations with financial or destructive consequences are guarded by confirmation. Launching a simulation, hard-stopping a run, starting a desktop, resuming a run, and deleting storage require approval. Local-only file tools include case inspection, folder upload, and result download; hosted use substitutes temporary file links.

Setup and configuration

The cloudHPC MCP server requires Python 3.10 or newer, a cloudHPC account, and an API key. Install it from the Git repository with either pipx install git+https://github.com/CFD-FEA-SERVICE/cloudhpc-mcp or pip. The installation provides the cloudhpc-mcp executable.

Set CLOUDHPC_APIKEY in the MCP client's environment. If that variable is absent, the server reads ~/.cfscloudhpc/apikey. Keep the API key private because it grants full access to the account.

For local clients, configure the command and environment variable as a standard stdio MCP server. Claude Desktop, Claude Code, ChatGPT desktop where MCP servers are available, Codex CLI, Gemini CLI, and VS Code Copilot agent mode are documented connection targets. The hosted endpoint requires no local installation and supports OAuth sign-in or an API key sent in a header.

Limitations and notes

The server depends on cloudHPC availability and account permissions. The API key provides full account access, so it should not be exposed in prompts or shared configuration. Remote desktops continue to incur charges until stopped, and simulation launches, hard stops, and storage deletion can change account data or billing state.

The hosted endpoint cannot access local paths. Use the local installation when an assistant must inspect a case folder directly or write downloaded results beside it. Resume support is documented for FDS and OpenFOAM and preserves the original solver, vCPU choice, RAM type, and folder.

Read the full README →View source on GitHub →

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Adoption & maintenance

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Last commit

1d ago

Most recent push to the default branch.

Tools exposed

Callable tools this server registers over MCP.

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Frequently Asked Questions about CloudHPC

cloudHPC is an MCP server that connects AI assistants to the cloudHPC engineering simulation platform. Its main tools inspect cases, recommend vCPU and RAM resources, guide solver setup, launch and monitor runs, synchronize or download results, manage storage, and open remote desktops for post-processing.

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