RAGents
Production-ready agentic RAG framework featuring intelligent decision trees, Logic-LLM integration, multimodal processing, and enterprise observability
RAGents represents the next generation of Retrieval-Augmented Generation frameworks, specifically designed for production environments where intelligent reasoning, multimodal processing, and enterprise-grade reliability are paramount. Unlike traditional RAG systems that rely on simple retrieval patterns, RAGents introduces sophisticated agent architectures that can reason through complex problems, make decisions based on configurable logic trees, and optimize their own performance through advanced techniques.
⚡ 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/ragents — read its card at https://meshkore.com/agent/ragents/.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/ragentsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ragents/.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 RAGents?
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.