RAGDoc_Assistant
Developed An AI-powered Retrieval-Augmented Generation (RAG) Document Assistant that allows users to upload PDF, DOCX, and TXT files and ask questions in natural language...
An AI-powered Retrieval-Augmented Generation (RAG) Document Assistant that allows users to upload PDF, DOCX, and TXT files and ask questions in natural language. The application retrieves relevant document content using semantic search and generates accurate answers with Google Gemini AI while displaying reference sources.
⚡ 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/yatendra-gupta193-ragdocassistant — read its card at https://meshkore.com/agent/yatendra-gupta193-ragdocassistant/.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/yatendra-gupta193-ragdocassistantFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/yatendra-gupta193-ragdocassistant/.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 RAGDoc_Assistant?
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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