GPT-RAG
GPT Retrieval-Augmented Generation
크롤링을 사용하지 않고 검색 api를 사용하기 위해 Bing search api를 사용했습니다. Request 요청을 하기 위해 request 패키지를 import 해서 사용했습니다. 사용자가 대화를 입력하면 bing_search 함수에서 Bing search api를 통해 request를 요청하고, 그 결과를 json 형태로 반환하게 됩니다. 반환된 json에서 필요한 부분인 snippet 부분들을 join해서 하나의 문자열로 만들어서 검색한 결과의 내용만 담게 됩니다.
⚡ 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/favorcat-gpt-rag — read its card at https://meshkore.com/agent/favorcat-gpt-rag/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/favorcat-gpt-ragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/favorcat-gpt-rag/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own GPT-RAG?
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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