CUDA-Q Docs

io.github.rogerawongPublished by GitHub account rogerawongv0.1.1Updated Oct 24, 2026

CUDA-Q docs, API reference, and runnable examples for AI agents, pinned to your installed version.

VerifiedSTDIODesktop onlyKnowledge & MemoryDeveloper Tools

Overview

AI-generated overview

Serves version-pinned NVIDIA CUDA-Q docs, API reference and runnable examples to an AI assistant through local full-text search.

What you can do
  • Search documentation and read full pages as clean markdown
  • Resolve exact Python or C++ API symbols with kind, doc URL and excerpt
  • Find complete runnable example programs from the matching CUDA-Q release
  • List execution targets (simulators, hardware providers, clouds) with selection guidance
  • Expose installed and indexed versions plus the served llms.txt as resources
When to use it
Useful when an assistant writes or debugs CUDA-Q quantum code and tends to cite renamed APIs, retired target names or install steps for the wrong version. It keeps answers aligned with the cudaq package actually installed.
Requirements
Runs locally over stdio via uvx or pip (Python package cudaq-docs-mcp). No API keys or embeddings. On first use it downloads a prebuilt index of a few megabytes; versions without a prebuilt asset need a local build. Optional environment variables CUDAQ_DOCS_MCP_AUTOBUILD and CUDAQ_DOCS_MCP_CACHE.
Before you install
The first run downloads an index from the network, and examples are fetched from GitHub release tags. Building an index locally takes time and disk space in the cache directory. It is a community project, not affiliated with or endorsed by NVIDIA.

Installation

In SourceWeft

  1. Open CUDA-Q Docs in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

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:

bash
uvx cudaq-docs-mcp build --version 0.14.0

Claude Code

bash
claude mcp add cudaq-docs -- uvx cudaq-docs-mcp

Claude Desktop (claude_desktop_config.json), Cursor (.cursor/mcp.json), or any client that takes a JSON server map:

json
{  "mcpServers": {    "cudaq-docs": {      "command": "uvx",      "args": ["cudaq-docs-mcp"]    }  }}

VS Code (.vscode/mcp.json):

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

ToolWhat 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:

  1. An explicit version argument ("0.15.0", "latest")
  2. The installed cudaq package, detected from distribution metadata (cudaq is never imported)
  3. 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.inv is 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

bash
cudaq-docs-mcp            # serve MCP on stdio (what clients run)cudaq-docs-mcp build      # build the index for your installed cudaq, else latestcudaq-docs-mcp build --version 0.15.0cudaq-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.

Source: README.md at commit e9abee0

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.1LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts