The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Mrd listing page.
Typed, datasheet-sourced specifications for 2,486 flight hardware products across 24 categories — reaction wheels, star trackers, propulsion, radios, antennas, structures, ground stations and more — with 19,011 values that each cite the datasheet page they came from.
Built for software and AI assistants, not only for reading. Ask in plain language, filter by engineering requirements, or download the whole thing.
Three rules make the data usable by a machine:
L0 machine-extracted, L1 verified by a human against the vendor datasheet.Hosted — no install. Add this as a custom connector in Claude, ChatGPT (developer mode) or any MCP client:
Local — for editors that speak stdio (Cursor, Windsurf, VS Code, Claude Desktop). Add to your MCP config:
The package is a thin bridge: it speaks stdio to your editor and forwards to the hosted endpoint, so new tools appear without upgrading anything.
Three tools arrive in the assistant:
| tool | what it does |
|---|---|
match_components | reverse search — requirements in, candidates grouped A / B / C with per-parameter verdicts |
get_component_specs | the full typed layer of one category, for your own comparison or trade study |
build_budget | mass and steady-state power of a stack, with bus-voltage checks and an honest list of what could not be counted |
io.github.newspacemarket-com/mrdinfo-zrja/newspace-mrd,
one-click install into Claude, Cursor, VS Code and other clientsNo authentication for reading. An optional free key raises rate limits five-fold — request one at /mrd-connect/.
examples/python/select_wheels.py — reverse search, printing why each candidate passed or failedexamples/python/budget.py — assemble a stack and budget it through the MCP toolsexamples/js/match.mjs — same search from Node, no dependenciesexamples/curl.md — every endpoint as a one-linerOpenAPI 3.1: openapi.json, served live at
https://newspacemarket.com/mrd-connect/openapi.json. Import it as a ChatGPT
Custom GPT Action, a LangChain / CrewAI / n8n toolkit, or convert it to Gemini
function declarations.
data/ holds a dated snapshot, regenerated as the layer grows:
| file | contents |
|---|---|
mrd-full.json | everything — products, values, property dictionary |
mrd-values.csv | one row per value: product, property, number, unit, bound, condition, source, confidence |
mrd-products.csv | one row per product: name, manufacturer, category, URL |
mrd-properties.csv | the property dictionary — what each key means and its canonical unit |
Live data is always newer than the snapshot; use get_component_specs or
/mrd-connect/specs?category=… when freshness matters.
Values are extracted from vendor datasheets (text and, for scanned documents, page images), from vendor product pages, and from product descriptions — the source of every record says which. Units are converted by code, not by a model: kg to g, dBm to W, psi to bar, tf to mN. A validation pass rejects a figure whose unit does not match the property, and an outlier scan flags values that sit far from the category median for human review.
Coverage is not exhaustive. Where a vendor publishes nothing machine-readable, the product simply is not here — and where a required field is missing, the API says so by name instead of guessing.
LICENSE.data/: CC BY 4.0, attribution "NewSpace Market" — see
data/LICENSE-DATA.Specifications are extracted from publicly published vendor materials and are provided as-is. Verify against the vendor datasheet before committing to a design.
Are you a vendor whose products are listed? Completing the missing fields takes minutes and is free — write to us from your company domain and we will send a direct link.