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SHADDAI Agents MCP

Use your 7 SHADDAI agents — with their real tools and agentic loop — inside Claude Code, Cursor, or any MCP client. Zero dependencies. It proxies to your running SHADDAI backend.

The agents

Agent

Specialty

SHADDAI

Supreme Orchestrator — strategy, coordination

NEXUS

Technical Architect — runs code (JS/Python), GitHub, security scans

ZEROX

Wealth & Revenue — live prices, DeFi, trade math

ORACLE

Research & Intelligence — web/wiki/arxiv/reddit + synthesis

TURTLE

UI/UX & Creative — images, palettes, diagrams

QUILL

Writing & Communication — copy, docs, translation, publishing

PIKADON

Security & Compliance — code audits, security checks

Related MCP server: nvidia-nim-mcp

Tools it exposes

  • shaddai_list_agents — list the 7 agents + what they do

  • shaddai_ask — quick single reply from a chosen agent

  • shaddai_task — a real agentic job: the agent uses its tools over multiple steps and returns the finished work

  • nvidia_skills — the curated NVIDIA/skills library (48 entries): the whole catalog, or one skill's full SKILL.md body

The NVIDIA skills library

A curated 48-skill slice of NVIDIA/skills, installed locally and exposed as a tool.

Category

Count

What it covers

tao

22

TAO data services, AutoML, DEFT loops, dataset formats

climate

7

Earth2Studio deterministic forecasts and diagnostics

physical-ai

5

Defect generation, video augmentation, infrastructure

omniverse

4

USD/SimReady/CAD-to-SimReady workflows

meta

3

Skill discovery and environment setup

rag

3

NVIDIA RAG Blueprint deploy/configure/troubleshoot

vision

2

FoundationPose perception pipeline

cosmos

1

Cosmos AnomalyGen synthetic defect generation

data

1

TAO dataset conversion and validation

25 of the 48 require an NVIDIA GPU to complete their stated execution path; the other 23 run CPU-only. Every GPU-flagged entry carries a gpuReason naming the exact step that needs the GPU.

The catalog lives at ~/.agents/skills by default. Point it elsewhere with SHADDAI_NVIDIA_SKILLS_ROOT.

Call it three ways:

  • List all — nvidia_skills with no arguments returns every skill with its id, category, GPU flag and S.A.P. relevance.

  • Read one — nvidia_skills with skill=<id> returns that skill's full SKILL.md body.

  • Filter — nvidia_skills with query=<text> keyword-matches over id, name, description and S.A.P. relevance; category=<name> filters by category.

Only skill ids listed in nvidia-skills.json can be read, ids are charset-restricted, and the resolved path must sit directly inside the catalog root — path traversal is rejected before any filesystem access.

Rebuilding the manifest

nvidia-skills.json is generated, not hand-edited:

npm run build:manifest   # rebuild from the local skill catalog
npm run sync:manifest    # copy it to the shaddai-mcp repo
npm test                 # 16-check stdio JSON-RPC harness

Setup

Your SHADDAI backend must be running (double-click START-SHADDAI.bat → serves http://localhost:3000).

Claude Code:

claude mcp add shaddai -- node "C:/Users/Brittany/mcp-servers/shaddai-agents/mcp.js"

Claude Desktop / Cursor (claude_desktop_config.json / .cursor/mcp.json):

{ "mcpServers": { "shaddai": { "command": "node", "args": ["C:/Users/Brittany/mcp-servers/shaddai-agents/mcp.js"], "env": { "SHADDAI_URL": "http://localhost:3000" } } } }

SHADDAI_URL defaults to http://localhost:3000; set it if you host SHADDAI elsewhere.

Security

  • stdout carries only JSON-RPC (logs go to stderr). Inputs are length-capped. It only talks to the backend URL you configure. MIT licensed.

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