mcp_rag_go
The MCP-RAG project is an AI agent framework based on the Multi-Context Protocol that connects various data sources (MySQL, documents, RAG search) with LLMs. It supports HTTP API, SSE chat, an MCP router, batch workers, and a React + Tailwind frontend.
Proyek ini adalah Proof of Concept Multi Context Protocol (MCP) dan Retrieval-Augmented Generation (RAG) untuk industri migas. Aplikasi ini menghubungkan berbagai sumber internal domain (drilling, production, HSSE, purchase order, timeseries, dan RAG search) ke dalam satu router, sehingga query dari client bisa diarahkan otomatis ke service/repository yang tepat.
⚡ 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/kukuhtw-mcpraggo — read its card at https://meshkore.com/agent/kukuhtw-mcpraggo/.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/kukuhtw-mcpraggoFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/kukuhtw-mcpraggo/.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 mcp_rag_go?
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
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