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#MCP and tool use

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Oct 31

Saturday

Oct 30

Friday

Oct 29

Thursday
  1. Quoting Ben Hylak

    Ben Hylak argues that every product he uses should be a headless MCP feeding into an agent, so users never have to think about what lies underneath — except for his own product, whose customers love its UI.

  2. Building an Agentic AI Platform on Amazon Bedrock AgentCore

    Stand up a governed, multi-account Agentic AI Platform on Amazon Bedrock AgentCore. This post walks through the architecture and an open-source reference blueprint: the operating model, control plane, per-Workstream cells, separate inference and tool gateways, and a CI/CD evaluation pipeline that gates each agent before production.

Oct 27

Tuesday

Oct 25

Sunday

Oct 24

Saturday
  1. How Bayer Crop Science built an agentic decision engine on Amazon Bedrock AgentCore with AWS Unified Operations

    Bayer Crop Science built the Agentic Decision Engine (ADE), a multi-agent platform on Amazon Bedrock AgentCore that lets breeders, analysts, and researchers ask natural language questions about their analytics platform. This post covers the ADE architecture, five design decisions, and how the team prepared it for production with AWS Unified Operations.

Oct 23

Friday
  1. Donating Agent Skills to the Agentic AI Foundation

    Donating Agent Skills to the Agentic AI Foundation News today from Anthropic: We’re committed to keeping Agent Skills open, community-driven, and vendor-neutral. Today, we are donating the standard to the Agentic AI Foundation (AAIF) under the Linux Foundation, which we co-founded with Block and OpenAI last year, and to which we donated the Model Context Protocol (MCP).

Oct 22

Thursday

Oct 21

Wednesday
  1. Mistral AI launches Voxtral 3, a full voice agent stack that listens, thinks, and talks in real time

    Mistral AI launched Voxtral 3, a new family of language models built for real-time voice agents. The system combines speech-to-text, text-to-speech, and a voice agent SDK, supports more than 50 languages, and lets agents tap into external tools during live conversations. It can run on your own infrastructure or through EU-hosted APIs to keep data under your control.

  2. Build a semantic layer for agentic AI on AWS with Denodo and Amazon Bedrock AgentCore

    Build a governed semantic layer for agentic AI on AWS with the Denodo Platform and Amazon Bedrock AgentCore. It federates Amazon Aurora, Amazon Redshift, and an on-premises PostgreSQL database into a single customer 360 view an agent queries in VQL, with identity propagation and row- and column-level access control enforced at the semantic layer.

  3. Securing AI agent identity with X.509 PKI on AWS

    Learn how to secure multi-agent AI systems with cryptographic identity using Keyfactor EJBCA and AWS services. This reference architecture combines signed request envelopes, user-signed delegation assertions, RFC 8693 audience-scoped tokens, and real-time OCSP revocation to prove agent identity and prevent request forgery across agent-to-agent and MCP tool calls.

  4. Discover tools at runtime with AWS Agent Registry

    Hardcoded tool wiring breaks down as an agent's catalog grows from a handful of tools to hundreds. This post walks through a runtime Discover, Instantiate, Execute loop built on AWS Agent Registry, where an orchestrator discovers MCP servers and A2A agents through semantic search at runtime instead of compiling every tool at build time.

  5. From data to decisions: Conversational supply chain intelligence with Amazon Quick and Amazon Bedrock AgentCore

    Enterprise supply chains are data-rich but insight-poor, with the data to decide scattered across ERP, monitoring, procurement, and email. This post shows how Amazon Bedrock AgentCore exposes those systems as a governed tool layer, and how Amazon Quick turns them into one conversational experience for business users, with a deploy-it-yourself walkthrough.

Oct 20

Tuesday

Oct 19

Monday