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cuda4cpu

OCI · GHCR.IO/JAVIER-CABEZAS/CUDA4CPU

Compile, run and check CUDA and HIP kernels without a GPU: wrong results, races, memory errors

+4 this week 40 Trust /100

Last scanned (1 day ago)

Scores higher than 43% of OCI servers

Category Testing and QA

Trust breakdown (7 categories)

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. How we score → Why this is hard to score →

Supply Chain Security0
  • No malware scan is available for this kind of package: the supply-chain vendors we use do not cover it. This is a permanent gap in our coverage, not a finding about the package.Unverified
  • Known CVEs could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
  • Install-script risk not yet assessed.Unverified
  • Dependency health could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
Provenance & Transparency45
Schema Quality & AI Usability56
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 1605 tokens (~321/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management30
  • Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities60
  • Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail

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.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 4 Nov 26 +1
    • Package version: 0.4.1 → 0.5.0 functional
  • 2 Nov 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Oct 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

  • 29 Oct 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Oct 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 0 to 3. That category is still filling its 30-day observation window: 0 days of observed history at the previous scan, 1 at this one. The score rises as the window fills, whether or not the server changes.

  • 26 Oct 26 35

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 4 Nov 2026 · Analysed oci/ghcr.io/javier-cabezas/cuda4cpu@0.5.0

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem oci
Reason No attestation published

Background: How many MCP packages publish verified provenance →

MCP tools · 5 exposed · ~1,449 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
capabilities ~36

What cuda4cpu implements of CUDA and HIP, what it does not, and how its checks work: read it before relying on a feature.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

check ~478

Look for bugs in a CUDA or HIP program without a GPU. Runs it with the threads of each block in several orders (forward, reverse, random with several seeds, warp orders): a result that changes with the order means a missing __syncthreads() or __syncwarp(), or a race. Also reports cuda4cpu's checks (divergent barriers and warp operations, copies in the wrong direction, allocations never freed), runs once with new allocations filled with 0xff bytes (a changed result means reads of memory never written), and runs a build with AddressSanitizer and UBSan (out-of-bounds and use-after-free accesses, undefined behavior), with source lines. The program should check its own results or print them; output that varies between identical runs (timings) is compared by exit code only, unless ignore_patterns removes the lines that vary.

NameTypeReqDescription
argsarray–The program's arguments
environmentobject–More environment variables for the program
filesobject–Sources by file name (relative paths) and their contents: .cu or .hip files, .cpp host files, and headers they include
ignore_patternsarray–Regular expressions of output lines to leave out of the comparison between orders, such as timings
languagestring–cuda (cuda4cpu-nvcc, the default) or hip (cuda4cpu-hipcc, the default when a source is a .hip file)
optionsarray–Compiler options, as nvcc's (-arch, -Xcompiler, -std, -I, -D, ...) or hipcc's; GPU options are accepted and ignored. Default -O2 -g.
pathsarray–Existing source files to compile where they are
sanitizersboolean–Also run with AddressSanitizer and UBSan (default true)
seedsarray–Seeds of the random orders (default 1, 2, 3)
stdinstring–Input for the program
timeout_secondsnumber–Time limit for each run (default 60, at most 600)
working_directorystring–Where the program runs: by default, the directory of the last path given, or the directory of the inline files

No output schema declared.

No examples provided.

compile ~203

Compile CUDA or HIP sources with cuda4cpu, as nvcc or hipcc would: whether they build, the compiler's diagnostics at the sources' own lines, and the features the sources use that cuda4cpu does not implement (textures, inline PTX, CUDA libraries, ...).

NameTypeReqDescription
filesobject–Sources by file name (relative paths) and their contents: .cu or .hip files, .cpp host files, and headers they include
languagestring–cuda (cuda4cpu-nvcc, the default) or hip (cuda4cpu-hipcc, the default when a source is a .hip file)
optionsarray–Compiler options, as nvcc's (-arch, -Xcompiler, -std, -I, -D, ...) or hipcc's; GPU options are accepted and ignored. Default -O2 -g.
pathsarray–Existing source files to compile where they are

No output schema declared.

No examples provided.

run ~277

Compile and run a CUDA or HIP program on the CPU: its exit code, output, and the problems cuda4cpu reports (divergent barriers, copies in the wrong direction). Use check to look for bugs.

NameTypeReqDescription
argsarray–The program's arguments
environmentobject–More environment variables for the program
filesobject–Sources by file name (relative paths) and their contents: .cu or .hip files, .cpp host files, and headers they include
languagestring–cuda (cuda4cpu-nvcc, the default) or hip (cuda4cpu-hipcc, the default when a source is a .hip file)
optionsarray–Compiler options, as nvcc's (-arch, -Xcompiler, -std, -I, -D, ...) or hipcc's; GPU options are accepted and ignored. Default -O2 -g.
pathsarray–Existing source files to compile where they are
stdinstring–Input for the program
timeout_secondsnumber–Time limit for each run (default 60, at most 600)
working_directorystring–Where the program runs: by default, the directory of the last path given, or the directory of the inline files

No output schema declared.

No examples provided.

test_kernel ~455

Test one kernel without writing a program: give its source, the launch configuration, its arguments (scalars, and arrays with their data, given or generated), and the expected outputs, as values or as a host reference function. A generated program launches the kernel, compares each output (exactly for integers, within a tolerance for floating point) and reports the elements that differ. With check (the default), it also runs in the thread orders and with the sanitizers that check uses.

NameTypeReqDescription
argumentsarrayyesThe kernel's arguments, in order
blockinteger|arrayyesThreads per block: a number or [x, y, z]
checkboolean–Also run in other thread orders and with the sanitizers (default true)
gridinteger|arrayyesBlocks: a number or [x, y, z]
kernelstringyesThe source of the kernel, with what it needs (device functions, includes, constants)
languagestring–cuda (cuda4cpu-nvcc, the default) or hip (cuda4cpu-hipcc, the default when a source is a .hip file)
namestringyesThe kernel to launch (a template with its arguments, e.g. scale<float>, works too)
optionsarray–Compiler options, as nvcc's (-arch, -Xcompiler, -std, -I, -D, ...) or hipcc's; GPU options are accepted and ignored. Default -O2 -g.
referencestring–C++ host code that defines void reference(...) with the kernel's parameters: it gets host copies of the inputs and writes the expected outputs into the output arrays (those without expected values)
seedsarray–As check's
shared_bytesinteger–Dynamic shared memory per block (default 0)
timeout_secondsnumber–Time limit for each run (default 60, at most 600)
toleranceobject–For floating-point outputs: an element matches if |got - expected| <= absolute + relative * |expected| (default 1e-5 and 1e-5)

No output schema declared.

No examples provided.

Install

How do I install the cuda4cpu MCP server?

cuda4cpu runs locally as a container image, launched with docker run --rm -i ghcr.io/javier-cabezas/cuda4cpu:0.5.0. Ready-made configuration for Claude, Cursor, VS Code, Codex and 3 more is on this page, copied from each client's own documentation.

oci · ghcr.io/javier-cabezas/cuda4cpu

# add to Claude Code
claude mcp add javier-cabezas-cuda4cpu -- docker run --rm -i ghcr.io/javier-cabezas/cuda4cpu:0.5.0
Common questions

What is the cuda4cpu MCP server?

cuda4cpu is an MCP server listed in the public MCP registry as io.github.javier-cabezas/cuda4cpu. Compile, run and check CUDA and HIP kernels without a GPU: wrong results, races, memory errors. This page covers its container image (ghcr.io/javier-cabezas/cuda4cpu).

Is the cuda4cpu MCP server safe to use?

cuda4cpu scores 40 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the cuda4cpu MCP server expose?

cuda4cpu exposes 5 tools: compile, run, check, test_kernel, capabilities. Their descriptions and schemas cost roughly 1,449 tokens of context every time the server is loaded.

Is the cuda4cpu MCP server still maintained?

cuda4cpu is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the cuda4cpu MCP server under?

cuda4cpu declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.