adaptive-rag-workbench
Sample for context-aware Agentic RaG, Q&A with multi-source verification, and self-curating knowledge base. Powered by Azure AI Foundry Agent Service, Azure AI Search with agentic retrieval and query rewrite, Semantic Kernel and LangGraph agents running in Azure Container Apps, and ready for Copilot Studio
Adaptive RAG Workbench is a comprehensive Microsoft solution accelerator that demonstrates three advanced Retrieval-Augmented Generation (RAG) patterns for enterprise AI applications. Built with Microsoft Agent Platform capabilities, including Azure AI Foundry Agent Service, M365SDK for Copilot Studio, and open source orchestration frameworks, this solution accelerator provides production-ready patterns for:
⚡ 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/azure-samples-adaptive-rag-workbench — read its card at https://meshkore.com/agent/azure-samples-adaptive-rag-workbench/.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/azure-samples-adaptive-rag-workbenchFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/azure-samples-adaptive-rag-workbench/.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 adaptive-rag-workbench?
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.