cloudHPC

cloud.cloudhpcPublished by cloudhpc.cloudOfficial publisherv0.8.1Updated Nov 7, 2026

Run FDS, OpenFOAM, CalculiX and other engineering simulations on cloudHPC from your AI assistant.

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Overview

AI-generated overview

Runs engineering simulations (FDS, OpenFOAM, CalculiX and more) on the cloudHPC cloud service from an AI assistant, from case inspection to results download.

What you can do
  • Inspect a local case folder, detect solver and model size, and get vCPU/RAM recommendations
  • Look up available solvers, machine options and per-solver case preparation guidance
  • Upload case folders, launch, resume, stop and live-tune running simulations
  • Follow runs, wait for completion, read logs and get diagnoses of known solver errors
  • Browse storage and results, download result archives, and create temporary upload/download links
  • Start and open a remote desktop for post-processing, and check API rate limits
When to use it
Useful when you run FDS, OpenFOAM, CalculiX, code_aster or similar solvers on cloudHPC and want to prepare, launch, monitor and retrieve runs from a chat instead of the web app. Also handy for checking why a run failed or for sizing resources before spending money.
Requirements
A cloudHPC account and API key. Local install: Python 3.10 or newer plus the cloudhpc-mcp package, with the key in the CLOUDHPC_APIKEY environment variable or the cloudHPCexec key file. Hosted endpoint: OAuth sign-in or the X-API-Key header. Network access to cloudHPC; some clients need a raised tool timeout for long waits.
Before you install
The API key gives full access to the account, so keep it private. Launching, resuming, hard-stopping runs and remote desktops are billed per vCPU-hour to your account, and storage deletion removes files permanently; these actions ask for confirmation, and OAuth offers a read-only option. Simulation names, logs, file lists and costs are sent to your AI provider. Storage files are deleted automatically after 60 days.

Installation

In SourceWeft

  1. Open cloudHPC in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/cloud.cloudhpc%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "cloudhpc": {
      "type": "http",
      "url": "https://mcp.cloudhpc.cloud/mcp"
    }
  }
}

README

cloudHPC MCP server

Run engineering simulations on cloudHPC from AI assistants that support the Model Context Protocol (MCP): Claude, ChatGPT/Codex, Gemini, GitHub Copilot and others, from their desktop apps, terminal apps and, where supported, web apps. Inspect a local case, get vCPU/RAM advice, upload the folder, launch, monitor, diagnose errors and download the results, all from a conversation.

Supported solvers: everything available on cloudHPC (FDS, OpenFOAM, snappyHexMesh, DAFoam, code_aster, CalculiX, OpenRadioss/OpenCourant, SU2, openTELEMAC, LIGGGHTS, LAMMPS, Kratos Multiphysics, OpenLB, Palabos, FreeFEM, T-Flows, DualSPHysics, preCICE coupled OpenFOAM/CalculiX/code_aster, EnergyPlus, CONTAM, ...). Resource advice follows the cloudHPC scalability rules and run diagnosis follows the cloudHPC errors guide.

What you can ask

  • "Check the FDS case in this folder and tell me which resources to use."
  • "Run it on cloudHPC and download the results when it finishes."
  • "What is the status of my running simulations?"
  • "My last run failed: what went wrong?"
  • "My OpenFOAM run is converging well: extend endTime to 2000 without stopping it."

Safe first prompts

Start with questions that only read data, then move on to actions that cost money once you are comfortable with how the assistant works:

  1. "How do I prepare an OpenFOAM case for cloudHPC?" (no account needed)
  2. "List my last simulations and summarise their status."
  3. "Why did my last simulation fail? Check the log."
  4. "Which vCPU and RAM type should I use for an FDS model with 8 meshes and 2 million cells?"
  5. "What is in the storage folder of my last run, and which files are results?"

Only then: "Upload this case and launch it", "Resume simulation 1234". Every action that costs money or deletes data asks for your confirmation first, and the assistant shows you what it will do. With OAuth sign-in you can also connect with read-only access (see Sign-in with OAuth).

Tools

ToolWhat it does
inspect_case ¹Detect solver and model size of a local folder (FDS meshes/MPI groups, OpenFOAM cells, CalculiX nodes, ...) and run pre-flight checks
suggest_resourcesvCPU and RAM type recommendation, with reasoning
solver_guideHow to prepare a case for a solver: input files, what cloudHPC does automatically, restart, optional settings, parallelism, logs
list_solvers, list_machine_optionsAvailable solvers, vCPU counts and RAM types
upload_folder ¹Compress a local case folder and upload it to your storage
launch_simulationLaunch a run (asks for confirmation)
list_simulations, get_simulation, wait_for_simulationFollow your runs; finished runs include a diagnosis of known errors
sync_simulationUpload partial results of a running job
stop_simulationSoft or hard stop (asks for confirmation)
resume_simulationResume a stopped run with the same solver, vCPU, RAM type and folder (FDS and OpenFOAM; asks for confirmation)
start_desktopStart a Linux or Windows remote desktop for post-processing; billed until you stop it (asks for confirmation)
live_settingsWhat can be changed in a running simulation, the current content of those files and the state of previous live updates
update_running_simulationChange a running simulation without stopping it: OpenFOAM system/controlDict, fvSolution, fvSchemes; FDS <CHID>.stop; code_saturne RESU/<run>/control_file; OpenRadioss/OpenCourant <root>_0001.ctl. The files go to the _push folder of the case and a sync is requested automatically, so the machine applies them within a few minutes (asks for confirmation)
open_remote_desktopBrowser remote-desktop link of a running job
list_storage, list_resultsBrowse your storage and result archives
download_results ¹Download result archives and extract them locally
get_upload_link, get_download_linkTemporary links to upload/download single files
delete_storageDelete one or more files or folders (a folder with all its content) with a single confirmation; deletion is asynchronous and takes a few minutes (asks for confirmation)
api_usageAPI rate limits and calls used

Actions that cost money or delete data (launching a run, a hard stop, deleting from storage) always need your confirmation. In apps that support it (e.g. Claude Code) the server shows you a confirmation dialog directly, so the assistant cannot confirm on your behalf; in other apps the assistant shows you a summary and waits for your OK.

¹ Only with the local installation: they work on files on your computer. In web apps (hosted endpoint) use get_upload_link / get_download_link instead.

Installation

Requirements:

  • Python 3.10 or newer
  • A cloudHPC account and its API key: open your cloudHPC profile page (APIKEY docs). The key gives full access to your account: keep it private.

Install with pipx (recommended: isolated, and the command ends up in ~/.local/bin, easy to find for desktop apps):

bash
pipx install git+https://github.com/CFD-FEA-SERVICE/cloudhpc-mcp

or with pip:

bash
pip install git+https://github.com/CFD-FEA-SERVICE/cloudhpc-mcp

This installs the cloudhpc-mcp command. Find its full path, you may need it below:

bash
which cloudhpc-mcp          # Linux / macOSwhere cloudhpc-mcp          # Windows

The API key is read from the CLOUDHPC_APIKEY environment variable or, if that is not set, from the file ~/.cfscloudhpc/apikey created by cloudHPCexec.

Connect your AI assistant

There are two ways to connect:

  • Local installation (desktop and terminal apps): the server runs on your computer, so it can read your case folders and save results next to them. All tools are available. Recommended.
  • Hosted endpoint (web apps): https://mcp.cloudhpc.cloud/mcp, nothing to install. You connect by signing in once with your API key (OAuth) or by sending the key in a header. It cannot read files on your computer: you upload cases and download results with temporary links (or from the cloudHPC web app). See Web apps.
AssistantDesktop appTerminal (Linux)Web app
ClaudeClaude Desktop (Windows, macOS, Linux beta)Claude Codeclaude.ai (custom connector)
ChatGPTChatGPT desktop app (where MCP servers are available)Codex CLIChatGPT (OAuth sign-in)
Gemininot supported: no Gemini desktop app with MCP supportGemini CLIGemini (OAuth sign-in)
GitHub CopilotVS Code (Copilot agent mode)Copilot CLInot supported

In every example replace your-api-key with your key. If the assistant cannot find the cloudhpc-mcp command, write its full path instead (see Installation).

Claude

Claude Desktop

Open Settings > Developer > Edit Config and add the server to claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: use Edit Config to open the file
json
{  "mcpServers": {    "cloudhpc": {      "command": "cloudhpc-mcp",      "env": { "CLOUDHPC_APIKEY": "your-api-key" }    }  }}

Restart Claude Desktop. The cloudHPC tools appear in the tools menu of a new conversation.

Claude Code
bash
claude mcp add --scope user cloudhpc -e CLOUDHPC_APIKEY=your-api-key -- cloudhpc-mcp

--scope user makes it available in every folder. Check it with claude mcp list or /mcp inside Claude Code.

ChatGPT / Codex

ChatGPT desktop app

In recent versions of the ChatGPT desktop app: Settings > MCP servers > Add server, choose STDIO:

  • Command: cloudhpc-mcp
  • Environment variable: CLOUDHPC_APIKEY = your-api-key

The app shares its MCP configuration with Codex (~/.codex/config.toml, see below), so a server added in one is available in the other. Availability depends on app version and plan. The ChatGPT web app only supports remote connectors and cannot run this local server.

Codex CLI
bash
codex mcp add cloudhpc --env CLOUDHPC_APIKEY=your-api-key -- cloudhpc-mcp

or edit ~/.codex/config.toml:

toml
[mcp_servers.cloudhpc]command = "cloudhpc-mcp"tool_timeout_sec = 1900        # wait_for_simulation can wait up to 30 minutes
[mcp_servers.cloudhpc.env]CLOUDHPC_APIKEY = "your-api-key"

Check it with codex mcp list.

Gemini

Gemini CLI
bash
gemini mcp add -s user -e CLOUDHPC_APIKEY=your-api-key cloudhpc cloudhpc-mcp

or edit ~/.gemini/settings.json:

json
{  "mcpServers": {    "cloudhpc": {      "command": "cloudhpc-mcp",      "env": { "CLOUDHPC_APIKEY": "$CLOUDHPC_APIKEY" },      "timeout": 1900000    }  }}

$CLOUDHPC_APIKEY takes the key from your shell (export CLOUDHPC_APIKEY=...); timeout (milliseconds) lets wait_for_simulation wait up to 30 minutes. Check it with /mcp inside Gemini CLI.

The Gemini desktop and web apps do not support custom MCP servers.

GitHub Copilot

VS Code (Copilot agent mode)

Run MCP: Open User Configuration from the Command Palette (or create .vscode/mcp.json in a project) and add:

json
{  "inputs": [    { "type": "promptString", "id": "cloudhpc-key",      "description": "cloudHPC API key", "password": true }  ],  "servers": {    "cloudhpc": {      "type": "stdio",      "command": "cloudhpc-mcp",      "env": { "CLOUDHPC_APIKEY": "${input:cloudhpc-key}" }    }  }}

VS Code asks for the key once and stores it securely. Open Copilot Chat in Agent mode and enable the cloudHPC tools from the tools picker.

Copilot CLI

Edit ~/.copilot/mcp-config.json:

json
{  "mcpServers": {    "cloudhpc": {      "type": "local",      "command": "cloudhpc-mcp",      "args": [],      "env": { "CLOUDHPC_APIKEY": "your-api-key" },      "tools": ["*"]    }  }}

or use /mcp add inside a Copilot CLI session. The Microsoft Copilot app for Windows does not support custom MCP servers.

Other MCP clients

Configure a stdio server with command cloudhpc-mcp and the environment variable CLOUDHPC_APIKEY.

Web apps (hosted endpoint)

Endpoint: https://mcp.cloudhpc.cloud/mcp (streamable HTTP). Two ways to authenticate:

  • Sign in with OAuth (ChatGPT, Gemini, claude.ai and any client that supports OAuth for MCP servers): see Sign-in with OAuth.
  • API key header: the client sends your key with every request in the X-API-Key header (or Authorization: Bearer <key>). The endpoint stores nothing: the key is only forwarded to the cloudHPC API for that request.

What changes compared with the local installation:

  • inspect_case, upload_folder and download_results are not available: the hosted server cannot see your computer.
  • To upload a case, compress the content of the case folder (files at the root of the archive) and ask the assistant for an upload link (get_upload_link): it gives you a ready curl command. Or upload it from the cloudHPC web app.
  • To get results, ask for a download link (get_download_link).
Sign-in with OAuth

When you add the connector with OAuth, the assistant opens a cloudHPC sign-in page:

  1. Check the name of the app asking for access. It will be able to see your simulations and storage, upload files and launch or stop simulations, which are billed to your account.
  2. Paste your API key (how to find your API key).
  3. Optionally tick Read-only access: the assistant can then see simulations, storage and results, but cannot launch, stop, resume, upload, delete or open remote desktops. Useful to try the connector safely, or for colleagues who only need to follow the runs.
  4. Click Connect.

The assistant never sees the key: it receives tokens that expire after one hour and are renewed automatically for 30 days, then you sign in again. To revoke access for every connected assistant, regenerate the API key in your cloudHPC profile: access stops within an hour.

claude.ai

On plans with custom connectors: Settings > Connectors > Add custom connector, URL https://mcp.cloudhpc.cloud/mcp, then either:

  • leave the authentication on OAuth and sign in when asked (Sign-in with OAuth), or
  • choose No sign-in and under Request headers add X-API-Key = your-api-key.

Enable the connector in a conversation from the tools menu. The same connector is also available in the Claude desktop and mobile apps.

ChatGPT web

In ChatGPT, turn on developer mode and add a custom connector (app):

  • URL: https://mcp.cloudhpc.cloud/mcp
  • Authentication: OAuth

Then sign in on the cloudHPC page (Sign-in with OAuth).

Gemini web

In the Gemini app (gemini.google.com):

  1. Click Customise in the left sidebar.
  2. Open the Connectors tab.
  3. Click + Custom, enter the URL https://mcp.cloudhpc.cloud/mcp and click Next.
  4. Sign in on the cloudHPC page that opens (Sign-in with OAuth).

Gemini registers itself automatically: you do not need an OAuth client ID or secret. The connector then appears under Connected apps.

Copilot web

Microsoft Copilot and Copilot Chat on github.com do not support custom MCP servers.

Other clients using the hosted endpoint

Any MCP client that supports streamable HTTP with custom headers works, for example:

bash
claude mcp add --transport http cloudhpc https://mcp.cloudhpc.cloud/mcp \  --header "X-API-Key: your-api-key"
json
{ "mcpServers": { "cloudhpc": {    "httpUrl": "https://mcp.cloudhpc.cloud/mcp",    "headers": { "X-API-Key": "your-api-key" } } } }

(the second is the Gemini CLI format; VS Code uses "type": "http", "url" and "headers"; Codex CLI uses url and http_headers in config.toml).

Good to know

  • Upload layout: the content of the case folder is archived at the root of upload.tar.gz and uploaded into a storage folder with the same name as the local folder. Hidden files are skipped. Folder names must not contain , ( ) ' $ ~ " # or spaces.
  • Resources: FDS, CalculiX and code_aster start on highcpu; after a memory error move to standard, then highmem. OpenFOAM and other MPI-only solvers use highcore or hypercore. 1 vCPU on highcpu is never suggested for a solver: it has too little RAM to start.
  • Checking runs: a run can end as COMPLETED even if the solver failed. When a run ends the server scans its output for the errors listed in the errors guide and suggests the fix; after downloading, it also checks the solver's own logs (OpenFOAM log.*, FDS .out).
  • Costs are billed per vCPU-hour and shown in euro when a run ends.
  • Storage: files are deleted automatically 60 days after creation. Download your results.
  • Rate limits: 100 API calls/hour on free accounts, 500 on full accounts (no daily limit). The server reads the rate-limit headers and stops before exceeding them.
  • Your data: what the tools return (simulation names, logs, file lists, costs) is sent to the AI provider of the assistant you use, under your own account and its terms. For confidential projects check your provider's data settings (e.g. training opt-out, business plans). With the local installation your API key stays on your computer; the hosted endpoint only forwards it and stores nothing. With OAuth sign-in the assistant only holds encrypted, expiring tokens, not the key.

Troubleshooting

ProblemFix
The assistant does not see the cloudHPC toolsRestart the app after editing its configuration; in terminal apps check with /mcp or mcp list.
command not found / server fails to startUse the full path of cloudhpc-mcp (which cloudhpc-mcp). Desktop apps do not load your shell's PATH, conda or virtual environments.
Unauthorized: the API key is invalidCopy the key again from your cloudHPC profile page.
Hosted endpoint: Invalid header nameWrite the header exactly as X-API-Key: your-api-key (name, colon, space, key).
Sign-in page: "The API key was not accepted"Copy the key again from your profile (how to find it); paste only the key, without spaces.
The assistant asks for an OAuth client ID and secretRemove the connector and add it again with the URL https://mcp.cloudhpc.cloud/mcp: it registers automatically, no client ID or secret is needed.
The assistant asks you to sign in againNormal after 30 days, or after you regenerated the API key: sign in with the current key.
rate limit reachedWait for the next hour, or ask the assistant to check less often.
The wait for a run is cut offRaise the tool timeout of your client (see the examples above) or ask the assistant to wait in shorter steps.

Development

bash
git clone https://github.com/CFD-FEA-SERVICE/cloudhpc-mcpcd cloudhpc-mcppip install -e ".[test]"pytest            # offline tests with a mocked API

Server modes (CLOUDHPC_MCP_MODE):

ModeTransportUse
local (default)stdioDesktop and terminal apps on your computer
remotestreamable HTTPHosted endpoint; the API key comes with each request
remote + OAuthstreamable HTTPSet CLOUDHPC_OAUTH_SECRET (random value; comma-separated list to rotate) and CLOUDHPC_PUBLIC_URL (public base URL): adds OAuth 2.1 sign-in (PKCE, dynamic client registration and client ID metadata documents) where the user pastes the API key on a server page; tokens are encrypted, nothing is stored. Requests without credentials get 401 with the OAuth challenge; X-API-Key keeps working
publicstreamable HTTPKey-less guide endpoint (e.g. for a website chat bot): only solver_guide, list_solvers, list_machine_options, suggest_resources. The solver and machine catalog is read with the key in CLOUDHPC_CATALOG_APIKEY (a dedicated account with no data) and cached for CLOUDHPC_CATALOG_TTL seconds (default 3600); requests are limited to CLOUDHPC_PUBLIC_RATE_PER_MIN per client IP (default 60)

scripts/e2e_test.py runs the whole workflow against the real API with your account: it uploads a tiny FDS case and, with --confirm-costs, runs it on 1 vCPU for about a minute (--no-launch only uploads; --cleanup deletes the test folder at the end).

Support

License

Apache-2.0

Source: README.md at commit f275c84

Tools

0
This server asks you to sign in, so SourceWeft could not read its tools without an account and has not indexed them. What a connected account sees can depend on that account and its permissions.

Version history

9
  1. v0.8.1LatestNov 7, 2026
  2. v0.8.0Nov 6, 2026
  3. v0.7.9Nov 5, 2026
  4. v0.7.7Oct 20, 2026
  5. v0.7.6Oct 19, 2026
  6. v0.7.4Oct 17, 2026
  7. v0.7.3Oct 15, 2026
  8. v0.7.0Oct 15, 2026
  9. v0.6.4Oct 12, 2026

Score

85% of the applicable checks met

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  • DescriptionRequired15 pts
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