FullStackChatbot
Full stack LLM application created using React and FastAPI for document chatting
In this project, we build a chatbot application which takes a document file (pdf, txt, docx, csv) as an input and answers user's query. The goal of this application is to accurately provide answers based on the uploaded file. This application could be used as an assistant to quickly answer questions or summarize facts from files containing large amounts of text data, making our lives easier.
⚡ 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/shrishailsgajbhar-fullstackchatbot — read its card at https://meshkore.com/agent/shrishailsgajbhar-fullstackchatbot/.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/shrishailsgajbhar-fullstackchatbotFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/shrishailsgajbhar-fullstackchatbot/.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 FullStackChatbot?
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.