turbulence-modeling-resource
Provides access to NASA Langley Research Center's Turbulence Modeling Resource, including a catalog of standard turbulence-model verification and validation test cases and reference experimental or correlation data for selected cases.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@turbulence-modeling-resourcelist the airfoil cases with reference data and their Mach numbers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@pipeworx/turbulence-modeling-resource
Catalog of NASA Langley's standard turbulence-model verification and validation test cases (flat plates, airfoils, jets, a backward-facing step, the wall-mounted hump, shock/boundary-layer interactions, and more), plus reference data for the cases that publish an unambiguous experimental or correlation dataset.
Part of Pipeworx — an MCP gateway connecting AI agents to 1851+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.
Tools
tmr_cases(...)— the full case catalog (or one category): id, category, flow regime, documented Mach/Reynolds conditions, and whether reference data is available viatmr_reference_data.tmr_reference_data(...)— the reference (experimental or correlation) data for one case, where the case's own page unambiguously labels a file as the reference data rather than one of many turbulence-model CFD results.
Related MCP server: spacedata
Auth
Keyless. US government work — public domain.
Data sources
NASA Langley Research Center, Turbulence Modeling Resource — the standard set of verification cases (checking that a turbulence model is implemented correctly) and validation cases (checking that it reproduces real flow physics) used across the turbulence-modeling community: flat plates, bumps-in-channel, 2D and 3D airfoils, axisymmetric jets, a backward-facing step, a wall-mounted hump, shock/boundary-layer interactions, a supersonic square duct, the ONERA M6 wing, and a high-Reynolds-number channel flow.
The resource moved from its original NASA-hosted address to a GitHub Pages
site the publisher itself maintains; this pack reads from the current
address. Mach number and Reynolds number in the case catalog are filled in
only where a case's own page states them explicitly — a null means NASA's
page did not give that figure, not that the flow has no such condition.
Case directories hold dozens of files each — one per turbulence model's CFD
result, plus (for some cases) the actual experimental or correlation
reference data the models are checked against, named and linked distinctly
on the case's own page. tmr_reference_data only serves the latter kind,
and only for cases where that distinction is unambiguous from the page
itself; everything else stays unmapped rather than guessed at, which is why
only a handful of cases report reference_data: true today. Every file
follows the same plain-text, Tecplot-style convention: #-prefixed comment
lines, a variables="col1","col2",... header, optional zone, t="label"
sections, then whitespace-separated numeric rows — parsed generically in
src/index.ts rather than per-case.
tmr_reference_data's data_as_of is the upstream file's own Last-Modified
response header — never a date written into the pack at build time, which
would silently go stale. fetched_at is always this call's own timestamp, so
a caller still knows when Pipeworx last asked even on the rare response
without a Last-Modified header. tmr_cases' catalog_transcribed is a
different thing entirely: the case list and conditions are a plain array
transcribed from the publisher's pages at pack-build time, not re-fetched
live on every call, so it is named and dated separately rather than
borrowing data_as_of's meaning.
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"turbulence-modeling-resource": {
"url": "https://gateway.pipeworx.io/turbulence-modeling-resource/mcp"
}
}
}What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/turbulence-modeling-resource/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}Both URLs reach the same gateway and the same 1851+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
No MCP client? Call it over HTTP
curl -X POST https://gateway.pipeworx.io/v1/tools/tmr_cases \
-H 'Content-Type: application/json' \
-d '{"category":"validation-basic"}'No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/tmr_cases. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.
Standalone (no gateway account)
This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:
{
"mcpServers": {
"turbulence-modeling-resource": {
"command": "npx",
"args": ["-y", "@pipeworx/mcp-turbulence-modeling-resource"]
}
}
}Or run it directly to confirm it starts:
npx -y @pipeworx/mcp-turbulence-modeling-resourceIt speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call
for only this pack's tools — none of the shared meta-tools the gateway
connection above adds. Same source, same tools, no ask_pipeworx routing.
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Turbulence Modeling Resource data" })The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
This server cannot be deployed
Maintenance
Related MCP Connectors
Aircraft intelligence for AI agents: valuations with uncertainty bands, FAA registry lookups, cost of ownership, comparable aircraft, fleet search, airworthiness directives and STCs, market metrics and forecasts, verified value reports, pre-buy diligence checklists, logbook search and a watchlist. 38 tools; free tier with OAuth or a Windsock API key.
A read-only verified record of agent-operable GTM tools: search, fetch, compare, track changes.
Academic papers, reference verification and research data for AI agents.
AI Agent Source Registry. 288K+ curated sources for agentic search and discovery.
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables automated geometry editing and aerodynamic analysis using OpenVSP and VSPAero through natural language. Provides tools to modify aircraft geometry parameters and run computational fluid dynamics simulations programmatically.36MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI tools to browse all 14 NASA Space Apps 2026 challenges, get curated NASA datasets ranked by usefulness with their access requirements and runnable starter code, and search NASA's live CMR catalog. Read-only with no account or API keys required.MIT
- AlicenseBqualityCmaintenanceEnables AI agents to drive OpenFOAM end to end: cloning tutorials or custom cases, editing dictionaries, meshing and running solvers in the background, tracking convergence and job status, and analyzing results. It also renders flow images — slices, patches, streamlines, iso-surfaces and residual or force plots — back to the agent.25MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to search de-identified NASA aviation safety incident reports by keyword, date range, aircraft or flight phase, fetch a full narrative and coded fields by ACN, and list the thirty covered safety topics with their report counts and NASA update dates. Answers come from NASA's periodic Report Set PDFs parsed into a queryable store, so coverage is limited to those topics.MIT