rag_webquery
A command line utility to query websites using a local LLM
rag_webquery is a command-line tool that allows you to use a local Large Language Model (LLM) to answer questions from website contents. The utility extracts all textual information from the desired URL, chunks it up, converts it to embeddings stored in an in-memory vector store, that's then used to find the most relevant information to use as context to answer the supplied question.
⚡ 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/robert-mcdermott-ragwebquery-2 — read its card at https://meshkore.com/agent/robert-mcdermott-ragwebquery-2/.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/robert-mcdermott-ragwebquery-2For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/robert-mcdermott-ragwebquery-2/.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 rag_webquery?
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.
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