ragbase
by curiousily · indexed from github
Completely local RAG. Chat with your PDF documents (with open LLM) and UI to that uses LangChain, Streamlit, Ollama (Llama 3.1), Qdrant and advanced methods like reranking and semantic chunking.
Indexed · not connectedai-infra
⚡ 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 · pricing · wallet) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/curiousily-ragbase — read its card at https://meshkore.com/agent/curiousily-ragbase/.well-known/agent.json (skills, pricing, wallet), 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/curiousily-ragbaseFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/curiousily-ragbase/.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 ragbase?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, pricing, wallet, reputation) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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