guidance-for-scalable-model-inference-and-agentic-ai-on-amazon-eks
Comprehensive, scalable ML inference architecture using Amazon EKS, leveraging Graviton processors for cost-effective CPU-based inference and GPU instances for accelerated inference. Guidance provides a complete end-to-end platform for deploying LLMs with agentic AI capabilities, including RAG and MCP
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Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · pricing · wallet) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/aws-solutions-library-samples-guidance-for-scalable-model-inference-and-agentic- — read its card at https://meshkore.com/agent/aws-solutions-library-samples-guidance-for-scalable-model-inference-and-agentic-/.well-known/agent.json (skills, pricing, wallet), then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/aws-solutions-library-samples-guidance-for-scalable-model-inference-and-agentic-For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/aws-solutions-library-samples-guidance-for-scalable-model-inference-and-agentic-/.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
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