# CUDA-Q Docs (pypi · cudaq-docs-mcp)

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

- Trust score: 68/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-18

## Components

- pypi · `cudaq-docs-mcp`: 68/100 (this document), [markdown](https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp.md), [page](https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp)

## Channel facts

- Registry: `pypi`
- Package: `cudaq-docs-mcp`
- Version: `0.1.1`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-18.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it.
  - 2 of 33 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (Apache-2.0).
  - Actively maintained (last published 6 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 88/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 700 tokens (~100/item across 7 items; 5 tools + 2 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 67/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 0% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### Claude

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

### Codex

```bash
codex mcp add rogerawong-cudaq-docs-mcp -- uvx cudaq-docs-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "rogerawong-cudaq-docs-mcp": {
      "type": "local",
      "command": [
        "uvx",
        "cudaq-docs-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add rogerawong-cudaq-docs-mcp --command uvx --arg cudaq-docs-mcp
```

### Hermes

```yaml
mcp_servers:
  rogerawong-cudaq-docs-mcp:
    command: "uvx"
    args: ["cudaq-docs-mcp"]
```

### Other

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

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-15 (score 68, 0)

- [functional regression] Security disclosure: unverified → fail

### 2026-08-14 (score 68, 0)

- [functional regression] Security disclosure: fail → unverified

### 2026-08-12 (score 68)

First indexed and scored.

## MCP tools (5)

### `search_docs` (~149 tokens)

Search the NVIDIA CUDA-Q documentation and return ranked excerpts.

Use this before answering any CUDA-Q question from memory: the platform
moves quickly and memorized APIs are often stale. Each result carries a
breadcrumb, an excerpt, and the canonical doc URL to cite.

Args:
    query: Natural language or keywords, for example "run kernel on GPU
        state vector" or "quantinuum credentials".
    version: Docs version such as "0.15.0" or "latest". Defaults to the
        installed cudaq version.
    limit: Maximum number of results (default 5).

Input parameters:

- `limit` (integer)
- `query` (string, required)
- `version`

### `get_page` (~76 tokens)

Fetch one documentation page as clean markdown.

Args:
    path: Page path as returned by search_docs, for example
        "using/quick_start" or "using/backends/sims/svsims".
    version: Docs version. Defaults to the installed cudaq version.

Input parameters:

- `path` (string, required)
- `version`

### `find_api` (~99 tokens)

Resolve a CUDA-Q API symbol to its canonical definition and doc URL.

Args:
    name: Symbol name, full or partial: "sample", "cudaq.observe",
        "qvector", "set_target".
    language: "python" or "cpp" to filter; omit for both.
    version: Docs version. Defaults to the installed cudaq version.

Input parameters:

- `language`
- `name` (string, required)
- `version`

### `search_examples` (~144 tokens)

Find complete, runnable CUDA-Q example programs.

Sources are the example, snippet, and application files shipped in the
CUDA-Q repository at the matching release. Prefer adapting these over
writing kernels from memory.

Args:
    query: What the example should show, for example "GHZ state",
        "VQE", or "noise model".
    language: "python" or "cpp" to filter; omit for both.
    version: Docs version. Defaults to the installed cudaq version.
    limit: Maximum number of examples (default 3).

Input parameters:

- `language`
- `limit` (integer)
- `query` (string, required)
- `version`

### `list_targets` (~101 tokens)

List CUDA-Q execution targets (backends) with guidance on choosing.

Covers simulators (CPU, GPU state vector, tensor network, noisy,
dynamics), quantum hardware providers, and cloud aggregators, each with
selection snippets and doc URLs. Call this when deciding where to run a
kernel or when the user names a provider.

Args:
    category: Optional filter: "simulator", "hardware", or "cloud".

Input parameters:

- `category`

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp#diagnostics

## Score history

- 2026-08-18: 68
- 2026-08-17: 68
- 2026-08-16: 68
- 2026-08-15: 68
- 2026-08-14: 68
- 2026-08-13: 68
- 2026-08-12: 68

## Links

- PyPI project: https://pypi.org/project/cudaq-docs-mcp/
- Socket report: https://socket.dev/pypi/package/cudaq-docs-mcp
- Repository: https://github.com/rogerawong/cudaq-docs-mcp
- Changelog RSS feed: https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp.json
- HTML version of this page: https://verifymcp.io/servers/rogerawong-cudaq-docs-mcp/cudaq-docs-mcp