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chinese-llm-models vs China Validators Toolkit

chinese-llm-models is a plugin bundle for AI coding tools published by aisa-one. Marketplaces we read that list it: 1 (Claude Code: claude-plugins-community). China Validators Toolkit is an MCP server published by tools.tutlab.tech. Marketplaces we read that list it: 1 (Official MCP Registry). As of our marketplace pass on 2026-10-22. 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
Marketplacechinese-llm-modelsChina Validators Toolkit
Claude Code: claude-plugins-community Listed
Version: 1.0.0
Forks (GitHub): 0
Stars (GitHub): 0
Not marked · First seen
Not listed
Official MCP Registry Not listed Listed
Version: 0.1.0
No figure published
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

chinese-llm-models vs China Validators Toolkit
Factchinese-llm-modelsChina Validators Toolkit
Marketplaces that list it11
Stars (GitHub) (differs)0No figure on GitHub
Forks (GitHub) (differs)0No figure on GitHub
Last releaseNot publishedNot published
Where it runs (differs)Installs as a plugin bundleRemote server (tools.tutlab.tech/mcp)
Transport (differs)Not statedStreamable HTTP
Tools it declaresNot publishedNot published
Environment variables it asks forNot publishedNot published
Parts of the bundle (differs)1Not a bundle
Licence (differs)MITNot stated
Repository (differs)github.com/aisa-one/aisa-providerNot stated
Changes in the last 7 days (differs)02
First seen (differs)2026-10-112026-10-18
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

chinese-llm-models

In its own words, on Claude Code: claude-plugins-community:

A unified API gateway that provides access to 6+ leading Chinese AI models (Kimi K2.5, Qwen3 Max, DeepSeek V3.2, GLM-5, MiniMax M2.1, Seed 1.8) through a single OpenAI-compatible endpoint. Features pay-per-use pricing, automatic cost tracking, and seamless integration with existing OpenAI client code.

China Validators Toolkit

In its own words, on Official MCP Registry:

China-focused validation tools: ID card, bank card, phone, plate, USCC, VIN, lunar calendar & more

How to run each

chinese-llm-models As a Claude Code plugin

Claude Code
/plugin marketplace add anthropics/claude-plugins-community
/plugin install chinese-llm-models@claude-community

China Validators Toolkit As a remote MCP server

Claude Code
claude mcp add --transport http agent-tools https://tools.tutlab.tech/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: chinese-llm-models · What it can do: China Validators Toolkit · Compare two other plugins

Data comes from the public marketplace file https://github.com/anthropics/claude-plugins-community/blob/HEAD/.claude-plugin/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