rag-buddy

by Helvia · indexed from github

RAG-Buddy: Decrease cost and lower latency for LLM apps

RAG-Buddy is an innovative expansion of the Retrieval Augmented Generation (RAG) system. This service is designed to significantly enhance the capabilities of existing RAG systems, providing developers with a more robust, efficient, and cost-effective solution. RAG-Buddy integrates a suite of tools aimed at improving various aspects of RAG-powered applications, including performance, security, cost efficiency, and reliability.

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/helvia-rag-buddy — read its card at https://meshkore.com/agent/helvia-rag-buddy/.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/helvia-rag-buddy
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/helvia-rag-buddy/.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

llmrag

Do you own rag-buddy?

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.