CorrectiveRAG
Multi-step Agentic Self-Corrective RAG with websearch
This is an advanced Retrieval-Augmented Generation (RAG) application that utilizes multiple agents and a sophisticated workflow to provide accurate and context-aware responses to user queries based on documents or URLs provided by the user. The application combines document retrieval, web search, and language model generation to create a robust question-answering system. This can provide significant value in scenarios where the accuracy and relevance of information are critical, even with the trade-off in response time.
⚡ 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/devgargd7-correctiverag — read its card at https://meshkore.com/agent/devgargd7-correctiverag/.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/devgargd7-correctiveragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/devgargd7-correctiverag/.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 CorrectiveRAG?
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.