aidc2026ai-melon/aidc-ai-mcp

**AI data center sizing, validation, and layout via a remote MCP server.**
AI 데이터센터 자동화 툴: 결정론적 엔진으로 AI 데이터센터를 설계·검증·레이아웃합니다.
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What is this?
This repository shows how to connect an MCP client or REST client to the
**AIDC-AI.IO Design Engine** — a deterministic, source-backed engine that sizes,
validates, and lays out Rubin-era AI data centers.
**What the engine does (on the server):**
- Accepts an IT load, rack density, GPU generation (Hopper / Blackwell / **NVIDIA Vera Rubin**
NVL72 / VR200), and site constraints.
- Returns deployment-unit-snapped rack counts, design PUE, power-factor-backed total MVA
(22.9 kV intake), liquid-cooling / air-cooling heat split, CDU planning values,
cost (KRW), and timeline.
- Validates designs against electrical, cooling, layout, safety, and data rules with
severity-classified findings and RFIs.
- Generates a rack-plan grid (hall dimensions, row/column positions in mm) and a
site-block layout.
**What this repo contains:**
- MCP client configuration snippet.
- curl and Node.js examples that call the public REST projection (/api/agent/*).
- Authenticated runnable examples that read the current response shape.
The core calculation engine, reference catalogs (rack library, AHJ/code matrix,
1.6T fabric topology, direct-to-chip (D2C) cooling models, etc.) are proprietary and
remain server-side. No engine source is published here.
> **Korea live.** Region-specific: 22.9 kV utility intake, Korean AHJ/code, climate,
> and operations validation. Keywords the engine targets: AI data center, AIDC,
> NVIDIA Rubin, Vera Rubin, 22.9kV, liquid cooling, CDU, D2C, 1.6T fabric, PUE.
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MCP Server
| Field | Value |
|---|---|
| Transport | Streamable HTTP |
| Endpoint | https://aidc-ai.io/api/mcp |
| Official registry name | io.aidc-ai/design-engine |
| Registry descriptor | remote.server.json (metadata revision 1.0.1; separate from npm/API versions) |
| Auth | Registered API key required. Configure Authorization: Bearer in the client credential settings; never send keys in tool arguments. |
| Tool count | 3 |
| Limits | The registered account limits apply; preserve HTTP 429 and Retry-After. |
Tools
| Tool | One-line description |
|---|---|
| design | Size an AI data center: returns rack count, PUE, total MVA, liquid/air cooling split, CDU count, cost (KRW), and build timeline. |
| validate | Check a design against electrical, cooling, layout, safety, and data rules; returns severity-classified findings and RFIs. |
| layout | Generate a rack-plan grid (hall dimensions, row/column positions in mm) and a site-block layout. |
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Quick Start
MCP client configuration
Obtain a registered integration key through AIDC Contact.
Use a client that supports Streamable HTTP and pass the key through its
credential settings as an Authorization: Bearer header. The mcp.json
example contains a replacement marker, not a working credential. Keep the
configured copy private and never commit a real key.
For a local stdio client, the published package is available through npm:
Set AIDC_API_KEY in the MCP server process's environment using your client's
secret or environment configuration. A file next to the server is not read
automatically. design, validate, and layout do not accept credentials
as tool inputs. Authentication errors are connection-configuration failures,