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NVIDIA vs io.github.mia-platform/console-mcp-server

NVIDIA is a plugin bundle for AI coding tools published by NVIDIA. Marketplaces we read that list it: 1 (Codex: openai-curated (openai/plugins)). io.github.mia-platform/console-mcp-server is an MCP server published by mia-platform. Marketplaces we read that list it: 1 (Official MCP Registry). As of our marketplace pass on 2026-10-13. This pair was picked by a reader, not by our comparison rule, so search engines are asked not to index the page.

Where each is published

Where each is published
MarketplaceNVIDIAio.github.mia-platform/console-mcp-server
Codex: openai-curated (openai/plugins) Listed
Version: 1.0.4
Forks (GitHub): 963
Stars (GitHub): 7 415
Not marked · First seen
Not listed
Official MCP Registry Not listed Listed
Version: 1.2.2
Downloads/month (npm): 208
Downloads/week (npm): 32
Forks (GitHub): 3
Stars (GitHub): 3
Not marked · First seen

Each figure is the marketplace's own and is never added up across marketplaces. A marketplace that publishes no figure shows none: no number is not zero.

The facts side by side

NVIDIA vs io.github.mia-platform/console-mcp-server
FactNVIDIAio.github.mia-platform/console-mcp-server
Marketplaces that list it11
Stars (GitHub) (differs)7 415 (better)3 (worse)
Forks (GitHub) (differs)963 (better)3 (worse)
Last releaseNot publishedNot published
Where it runs (differs)Installs as a plugin bundleRemote server (console.cloud.mia-platform.eu/console-mcp-server/mcp)
Transport (differs)Not statedStreamable HTTP
Tools it declaresNot publishedNot published
Environment variables it asks forNot publishedNot published
Parts of the bundle (differs)12Not a bundle
Licence (differs)Apache-2.0 AND CC-BY-4.0Not stated
Repository (differs)github.com/openai/pluginsgithub.com/mia-platform/console-mcp-server
Changes in the last 7 days00
First seen2026-10-112026-10-11
Endpoint at the last check (differs)no remote endpoint we checknot checked yet

Lines where the two differ have a tinted background and bold values. Where the data itself says which value is better (more marketplaces, a larger figure of the same marketplace, a fresher release, a verified mark on a marketplace that lists both), the better one is also marked green with ▲ and the worse one red with ▼. Where it runs, the transport, the tools, the settings, hooks, the bundle's parts, the licence and the week's changes are marked only as different: more or fewer is not better in itself.

What each says it does

NVIDIA

In its own words, on Codex: openai-curated (openai/plugins):

Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.

io.github.mia-platform/console-mcp-server

In its own words, on Official MCP Registry:

The official MCP Server from Mia-Platform to interact with Mia-Platform Console

How to run each

NVIDIA As a Codex plugin

Codex
codex plugin marketplace add openai/plugins

io.github.mia-platform/console-mcp-server As a remote MCP server

Claude Code
claude mcp add --transport http console-mcp-server https://console.cloud.mia-platform.eu/console-mcp-server/mcp --header "Authorization: Bearer <YOUR_TOKEN>"

Requires: Authorization header

Commands built only from what the marketplaces declare; the full set for every client is on each card.

Tools each declares

Neither one's marketplaces publish a list of tools, so there is nothing to compare.

Settings each asks for

Neither one's marketplaces publish the settings it asks for.

What it can do: NVIDIA · What it can do: io.github.mia-platform/console-mcp-server · Compare two other plugins

Data comes from the public marketplace file https://github.com/openai/plugins/blob/HEAD/.agents/plugins/marketplace.json. Data comes from the Official MCP Registry (registry.modelcontextprotocol.io), CC0 1.0. Figures come from our own regular passes over the marketplaces, last read on . We publish no contact details for plugin publishers.

Where the data comes from: how the catalog is built