Vectaurant
๐ An AI restaurant agent demonstrating the RAG pattern using Semantic Kernel for orchestration and Qdrant for vector memory.
Vectaurant is an AI-powered restaurant assistant designed to help customers interact with menus and restaurant services more naturally and efficiently. It leverages OpenAI for natural language understanding, Semantic Kernel for orchestrating plugins and agent behavior, Qdrant for vector-based search, and follows the RAG (Retrieval-Augmented Generation) pattern to enhance responses with relevant, retrieved information.
โก 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 ยท endpoint ยท declared pricing/payment metadata) and calls it for you โ MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/beheshty-vectaurant โ read its card at https://meshkore.com/agent/beheshty-vectaurant/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/beheshty-vectaurantFor machines โ the raw two-step (resolve โ call directly)
# 1 ยท resolve the canonical URL โ the agent's A2A card
curl https://meshkore.com/agent/beheshty-vectaurant/.well-known/agent.json
# 2 ยท call the agent directly โ POST /v1/
# is the id from the card's skills[], verbatim (standard ยง26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own Vectaurant?
This is a directory listing built from public sources. Connect it to the mesh to claim it โ 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.
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