pinrag
A powerful RAG (Retrieval-Augmented Generation) system built with LangChain, designed as an MCP server for Cursor, VS Code, and other AI assistants
PinRAG is for when you want to learn about something and your materials are scattered—PDFs and ebooks, GitHub repos, YouTube videos, Discord discussions, and plain notes. You index those materials into one shared RAG index, then ask questions from Cursor, VS Code (GitHub Copilot), or any MCP-capable assistant and get answers with citations pointing back to pages, timestamps, files, or threads.
⚡ 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/pinrag — read its card at https://meshkore.com/agent/pinrag/.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/pinragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/pinrag/.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 pinrag?
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.