Spec Driven Development
by formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Runs on your computer★ 440MITUpdated 14 months ago
Install
CUDA-Q Docs
Overview
Description from the maker (original English)
CUDA-Q docs, API reference, and runnable examples for AI agents, pinned to your installed version.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Other
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"cudaq-docs": {
"command": "uvx",
"args": [
"cudaq-docs-mcp"
]
}
}
}Run this in your terminal
claude mcp add cudaq-docs -- uvx cudaq-docs-mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"cudaq-docs": {
"command": "uvx",
"args": [
"cudaq-docs-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"cudaq-docs": {
"type": "stdio",
"command": "uvx",
"args": [
"cudaq-docs-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account rogerawong, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Otheri
- More stars than 0% of the other 18372 servers in this category
- Published to the registry more recently than 20% of the other 18372 servers in this category
- Basic checks equal to or better than 100% of the other 18372 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is CUDA-Q Docs safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 3 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Spec Driven Development, Remote Desktop Commander, A1RO — Irish employment tools
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Runs in the cloud★ 211Updated 2 days ago
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A1RO — Irish employment tools
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Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
cudaq-docs-mcp
An MCP server that serves NVIDIA CUDA-Q documentation, API reference, and runnable examples to AI agents: version-pinned to the cudaq you actually have installed.
Community project, not affiliated with or endorsed by NVIDIA. CUDA-Q is a trademark of NVIDIA Corporation.
Why
Quantum SDKs move faster than model training data. Ask an AI assistant to write CUDA-Q code and it answers from whatever it memorized: renamed APIs, retired target names, install steps for a version you do not run. The failure is version skew, and it lands where onboarding matters most: the first ten minutes.
This server gives any MCP-capable agent the current answer instead. Documentation search, exact API symbol resolution, complete runnable examples, and a backend-selection guide, all served from an index of the docs that match your installed cudaq package. No API keys and no embeddings: SQLite full-text search with BM25 ranking, on your machine, offline once the index exists.
Quick start
Register the server with your client; on first use it downloads a prebuilt index (a couple of megabytes) automatically. Building locally is only needed for versions without a prebuilt asset:
uvx cudaq-docs-mcp build --version 0.14.0Claude Code
claude mcp add cudaq-docs -- uvx cudaq-docs-mcpClaude Desktop (claude_desktop_config.json), Cursor (.cursor/mcp.json), or any client that takes a JSON server map:
{"mcpServers": { "cudaq-docs": { "command": "uvx", "args": ["cudaq-docs-mcp"] } } }
VS Code (.vscode/mcp.json):
{"servers": { "cudaq-docs": { "type": "stdio", "command": "uvx", "args": ["cudaq-docs-mcp"] } } }
Prefer pip? pip install cudaq-docs-mcp and use cudaq-docs-mcp as the command.
Tools
| Tool | What it returns |
|---|---|
search_docs(query, version?, limit?) | Ranked doc excerpts with breadcrumbs and canonical URLs |
get_page(path, version?) | One full documentation page as clean markdown |
find_api(name, language?, version?) | Exact Python or C++ symbol, kind, doc URL, and an excerpt |
search_examples(query, language?, version?, limit?) | Complete runnable programs from the CUDA-Q repository at the matching release |
list_targets(category?) | All 24 execution targets: simulators, hardware providers, and clouds, with selection snippets and when-to-use guidance |
Resources: cudaq://versions (installed and indexed versions) and cudaq://llms.txt (CUDA-Q's own llms.txt for the served version).
Version-pinned answers
Every tool resolves its docs version in this order:
- An explicit
versionargument ("0.15.0", "latest") - The installed cudaq package, detected from distribution metadata (cudaq is never imported)
latest
Indexes are per-version. When a pinned index is missing the server says so in the response and serves latest instead, with the one command that fixes it. Skew becomes visible instead of silent.
How it works
CUDA-Q publishes the raw material: a Sphinx inventory (objects.inv) listing every page and API symbol, markdown mirrors of each docs page, a per-version llms.txt, and example sources in the repository. This server builds on that groundwork:
objects.invis the crawl manifest and the API symbol table: no scraping heuristics- each markdown mirror is cleaned of theme chrome, code blocks are rebuilt with their language, and heading anchors are preserved for deep links
- pages are chunked by heading and indexed in SQLite FTS5 (porter stemming, BM25 ranking)
- examples, snippets, and application sources are fetched from the GitHub release tag that matches the docs version
The whole index is one SQLite file per version in your cache directory (cudaq-docs-mcp info shows where). A nightly workflow rebuilds the latest index so refreshes stay a download, not a build.
CLI
cudaq-docs-mcp # serve MCP on stdio (what clients run)cudaq-docs-mcp build # build the index for your installed cudaq, else latest cudaq-docs-mcp build --version 0.15.0 cudaq-docs-mcp info # cache location, indexed versions, detected cudaq
Set CUDAQ_DOCS_MCP_AUTOBUILD=1 to build automatically on first use, and CUDAQ_DOCS_MCP_CACHE to relocate the cache.
Roadmap
- Prebuilt indexes for pinned release versions, not just
latest - An eval set of real developer questions, with published retrieval scores
- CUDA-QX library docs
Contributing
Issues and PRs are welcome. Commits need a DCO sign-off (git commit -s); see CONTRIBUTING.md. Built in the open with Claude Code.
License
Apache-2.0. Documentation content belongs to NVIDIA Corporation & Affiliates, originates from the Apache-2.0 licensed NVIDIA/cuda-quantum repository, and every served result links back to the canonical page. See NOTICE.