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标签:#Model Context Protocol

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Presentation: Architecting the Data Layer for AI Agents: From Transactional Systems to MCP and Semantic Models

Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs across precision, security, and cost. Nardon details using data mesh, low-latency database architectures, semantic ontologies, and dynamic MCP tool selection to optimize context windows and reduce token overhead in transactional systems. By Fabiane Nardon

2026-08-29 原文 →
AI 资讯

Instacart Builds Blueberry, an AI-Powered Assistant to Help On-Call Engineers Investigate Incidents

Instacart introduced Blueberry, an AI-assisted incident response system that helps on-call engineers investigate production issues faster. It combines AI agents, operational data, and historical incident knowledge to generate grounded root cause hypotheses in Slack. It uses parallel subagents, MCP integrations, and incident history to reduce investigation time while keeping engineers in control. By Leela Kumili

2026-08-07 原文 →
AI 资讯

Azure API Management Adds Dedicated AI Gateway Tier, Governing Models and MCP Tools

Microsoft released a dedicated AI Gateway tier of Azure API Management in public preview, with a control plane built around models, MCP servers and tools rather than APIs. It fronts Foundry, Bedrock, Vertex AI and OpenAI behind one endpoint, with policy cards instead of XML. Architects welcomed the consolidation while questioning where the governance boundary sits. By Steef-Jan Wiggers

2026-08-07 原文 →
AI 资讯

Article: Securing MCP in Production: Defense-in-Depth Beyond the Gateway

This article presents a defense-in-depth approach for securing Model Context Protocol (MCP) deployments in production. It outlines four architectural control layers: safe execution, management infrastructure, outbound trust, and semantic integrity, arguing that production security requires enforcement beyond the gateway at the earliest trustworthy control points. By Nik Kale

2026-07-29 原文 →
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Article: An Evolutionary Architecture Pattern for Managing AI’s Pace of Change

Traditional API gateways assume deterministic services and simple schemas - assumptions agentic AI breaks. Discover why enterprise engineering leaders are adopting AI Gateways as an evolutionary architecture seam. Centralize guardrails, model routing, agent identity, action policy, and semantic audit within a single control plane to prevent costly incidents while keeping core platforms stable. By Joe Price, Branimir Đurek, Pavlos Migkiros, Trevor Dearham

2026-07-27 原文 →
AI 资讯

How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone

DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend data. Early results show up to 24% higher checkout conversion, 17% larger baskets, and improved intent accuracy using memory-backed sessions. By Leela Kumili

2026-07-13 原文 →
AI 资讯

AI Model Context Protocol Adds Centralised Auth for Enterprise

The Model Context Protocol team has promoted its Enterprise-Managed Authorisation extension to stable status, adding a centralised way for organisations to control access to MCP servers through their identity provider. The project states the aim is to replace per-server consent prompts with a zero-touch flow in which users sign in once and then access approved servers without further setup. By Matt Saunders

2026-07-06 原文 →
AI 资讯

Vercel Introduces Eve, an Open-Source Framework for Building AI Agents

Vercel has released Eve, an open-source framework for building, deploying, and operating AI agents in production. The framework uses a filesystem-based project structure to organize agent instructions, tools, skills, subagents, communication channels, and scheduled tasks, enabling developers to define agent behavior while reducing the amount of supporting infrastructure they need to implement. By Daniel Dominguez

2026-06-27 原文 →
AI 资讯

AI Agent Identity and Permission Challenges: How Uber and Auth0 Are Rethinking Access Control

Uber recently described an internal architecture for propagating identity across multi-agent AI workflows. The design aims to perserve user context, agent provenance, and scoped access as agents delegate work and call internal tools. The case study aligns with Auth0’s view that AI agents need permissions based on delegated authority, scoped credentials, and explicit human approval boundaries. By Eran Stiller

2026-06-17 原文 →
AI 资讯

Cloudflare Adds Support for Claude Managed Agents

Cloudflare recently added support for Claude Managed Agents, allowing developers to run and manage Claude agents within Cloudflare. Developers can connect agents to private systems, choose their runtime environment, and monitor agent activity using Cloudflare services. By Renato Losio

2026-05-28 原文 →