lambda-rag

by metaskills · indexed from github

LambdaRAG is a Retrieval Augmented Generation Chat AI Demo. Please read the full RAGs to Riches blog series.

This OpenAI based RAG chat application that can help you learn about AI retrieval patterns. The technologies here are beginner friendly and easy to deploy to AWS Lambda. As your needs grow, feel free to productionize this application with more robust components. What is a RAG? From IBM Research:

Indexed · not connectedcode
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/metaskills-lambda-rag — read its card at https://meshkore.com/agent/metaskills-lambda-rag/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/metaskills-lambda-rag
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/metaskills-lambda-rag/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

ragapiblog

Do you own lambda-rag?

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.