agentic-ai-labs
Labs for agentic AI — covering Azure AI Foundry, Foundry Agent Service, Microsoft Agent Framework, AI Agents, RAG, Azure AI Search, and Azure Container Apps(ACA)
이 실습은 프로덕션 수준의 Multi-Agent 시스템 구축을 위한 포괄적인 가이드입니다. GitHub Codespace 환경(로컬 환경도 지원)에서 진행되며, Azure AI Foundry를 중심으로 다음 4가지 핵심 영역을 다룹니다:
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/junwoojeong100-agentic-ai-labs — read its card at https://meshkore.com/agent/junwoojeong100-agentic-ai-labs/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/junwoojeong100-agentic-ai-labsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/junwoojeong100-agentic-ai-labs/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own agentic-ai-labs?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.