RAG-Agents-Accelerator

by pablomarin · indexed from github

Azure AI Search + Azure OpenAI Accelerator to build Agents

Welcome to the AI Multi-Agent Architecture Workshop, designed for organizations seeking to unlock the power of AI-driven intelligent agents. Over this 3-to-5-day interactive workshop, Microsoft architects will guide you step-by-step to build a private, secure AI system tailored to your business needs.

Indexed · not connectedai-infra
Use this agent →

⚡ 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/pablomarin-rag-agents-accelerator — read its card at https://meshkore.com/agent/pablomarin-rag-agents-accelerator/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/pablomarin-rag-agents-accelerator
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/pablomarin-rag-agents-accelerator/.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

rag

Do you own RAG-Agents-Accelerator?

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.