Regulated-industry AI compliance: EU AI Act, APRA, NIST AI RMF, ISO 42001, AU AI Safety.
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io.github.uchit/mcp-regulated-ai-compliance is an MCP server that regulated-industry AI compliance: EU AI Act, APRA, NIST AI RMF, ISO 42001, AU AI Safety. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 79/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"io-github-uchit-mcp-regulated-ai-compliance": {
"args": [
"-y",
"mcp-regulated-ai-compliance-http"
],
"command": "npx"
}
}
}Are you the author?
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Regulated-industry AI compliance: EU AI Act, APRA, NIST AI RMF, ISO 42001, AU AI Safety.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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No known CVEs.
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A Model Context Protocol server exposing the regulated-industry AI compliance knowledge from hellouchit.com as tools, resources, and prompts callable from any MCP-compatible AI client — Claude Desktop, Cursor, Zed, Windsurf, OpenAI ChatGPT, Continue, Cline, and ~40 other clients.
Free + open-source (Apache 2.0, dataset CC BY 4.0). Built by Uchit Vyas.
Disclaimer: This is a personal, open-source, non-commercial project. Views are my own. It is not affiliated with, endorsed by, or representative of my employer.
The OpenAI GPT Store hosts the EU AI Act and AU AI Safety Standard coaches as ChatGPT-only assets. The Claude Project equivalents are private to each user's Claude Pro account (no public sharing). Neither reaches the practitioners who work primarily inside Cursor, Zed, Continue, Cline, or the Claude API directly.
An MCP server is the only Claude-side asset that is genuinely shareable + multi-client. It surfaces the same dataset, anti-patterns, decision trees, and classification logic — but as tools any AI agent in any compatible client can call. One published server → 40+ client surfaces → the practitioner who never opens ChatGPT or claude.ai still ends up citing your work.
mcp-regulated-ai-compliance/
├── README.md ← you are here
├── scope/ ← the design docs (read FIRST)
│ ├── 00-product-brief.md What this is + who it's for
│ ├── 01-architecture.md System design + transport choices
│ ├── 02-tools-spec.md The 10 tools the server exposes
│ ├── 03-resources-spec.md The resources + prompts
│ ├── 04-distribution-strategy.md Where to list + how to get installs
│ └── 05-build-roadmap.md v0.1 → v1.0 in 4 phases
├── src/
│ ├── index.ts ← MCP server entry point (working stub)
│ ├── tools/ ← one file per tool
│ │ └── lookup-control.ts ← FULLY IMPLEMENTED as reference
│ ├── resources/ ← one file per resource type
│ ├── prompts/ ← pre-built prompt templates
│ ├── data/ ← embedded knowledge (dataset, anti-patterns, playbooks)
│ │ ├── dataset.json ← 56 controls × 28 regulations × 261 tools
│ │ ├── dataset.csv ← same data, CSV format
│ │ ├── anti-patterns.md ← 15 named failure modes
│ │ └── playbooks/ ← 90-day playbooks
│ └── lib/
├── docs/
│ └── install/ ← per-client install guides
├── examples/ ← sample conversations / use-cases
├── tests/
├── package.json ← npm config (working)
├── tsconfig.json ← TypeScript config
├── LICENSE ← Apache 2.0 (code) + CC BY 4.0 (dataset)
├── .gitignore
└── .github/workflows/ ← CI: build + publish to npm
v0.2.1 = data-source abstraction so the same codebase runs on Node (stdio, node:http) AND on Cloudflare Workers / Deno Deploy / Vercel Edge. See
worker/for the Cloudflare scaffold.
[![Provenance](https://img.shields.io/badge/npm-provenance%20signed-success