AgentCore

AWS published a walkthrough for connecting Claude Desktop on Amazon Bedrock to a managed, MCP-compatible Web Search capability through Amazon Bedrock AgentCore Gateway. According to AWS, the search is backed by an Amazon web index spanning tens of billions of documents, and query traffic stays within AWS infrastructure. Web Search is available in three AWS Regions; pricing is not disclosed in the post.

Amazon has released an updated Bedrock AgentCore runtime that holds cold start latency at roughly 2 seconds regardless of container image size, versus up to 30 seconds on the previous version. The update also changes memory billing to track real-time usage instead of peak allocation.

Wood Mackenzie built APEX (Agentic Platform for Energy eXperience) on Amazon Bedrock AgentCore to give three separate applications a shared runtime for identity, guardrails, memory, and scaling instead of each rebuilding the same infrastructure. The company says 88% of its internal AI proofs-of-concept never reach wide deployment, a gap it attributes to architecture rather than model quality.

AWS published a technical walkthrough for building MCP Apps—interactive HTML widgets rendered inside AI hosts like ChatGPT and Claude—using Amazon Bedrock AgentCore's runtime and Gateway components. The reference implementation, a unicorn rental app, demonstrates host-agnostic rich UI delivered through a single MCP server.

AWS's August 2026 roundup details Bedrock and AgentCore updates including million-token context for GPT-5.6 models, AgentCore runtime sessions lasting up to 14 days, OpenAI's new Daybreak Red/Blue cybersecurity models, and Claude Opus 5 availability in GovCloud with zero data retention.

AWS published a reference architecture showing how to deploy a WhatsApp ordering assistant on Amazon Bedrock AgentCore, using Nova 2 Lite for text and Nova 2 Sonic for voice, with shared cross-channel memory and MCP-based tool access to backend systems.

Amazon Bedrock AgentCore Evaluations now scores AI agents regardless of the framework they're built on, by reading OpenTelemetry and OpenInference instrumentation instead of requiring a specific SDK. The service automatically decodes traces from six named frameworks and extends coverage to any library following the same telemetry conventions.

Amazon Bedrock AgentCore now lets teams write agent governance rules in plain English and automatically convert them into Dogwood, an open-source policy language, including support for time-based and cumulative constraints. The update extends Policy Authoring beyond simple parameter restrictions to rate limiting, sequential tool-call ordering, and Amazon Bedrock Guardrails integration.

Amazon Bedrock AgentCore Payments, built with Coinbase and Stripe, is now generally available after a May preview. The service lets AI agents autonomously pay for paywalled content, APIs, and per-inference compute using stablecoin wallets with spending caps and audit logging.

Amazon Bedrock AgentCore now supports temporal policies—stateful authorization rules that evaluate an AI agent's entire session history, not just individual tool calls. The feature runs at the AgentCore Gateway, outside agent code, so it cannot be bypassed by prompt manipulation or agent bugs.

AWS published a technical breakdown of an MCP bridge that connects cloud-hosted AI agents on Amazon Bedrock AgentCore to MCP servers running on a user's local machine. The architecture, used internally in a finance assistant with over 41,000 conversations in its first year, tunnels MCP JSON-RPC messages through WebSocket and browser native messaging.

AWS has released AgentCore, a new platform for hosting and running voice-based AI agents, integrated with Amazon Nova 2 Sonic for real-time speech capabilities. The platform uses the open Model Context Protocol (MCP) to connect agents to backend systems and deploys each conversation in isolated microVMs.

AWS has published a technical implementation guide for automating healthcare claims processing using Amazon Bedrock Data Automation and Amazon Bedrock AgentCore. The pipeline extracts data from CMS-1500 claim forms, validates against AWS HealthLake records, and generates FHIR-compliant claim resources with automated notifications.

AWS published a technical guide for building voice appointment agents using Amazon Nova 2 Sonic, a speech-to-speech model that processes audio natively without separate transcription steps. The tutorial covers authentication, scheduling, and escalation tools running on Amazon Bedrock AgentCore with DynamoDB persistence.

Amazon Web Services launched Web Search on Amazon Bedrock AgentCore, a fully managed web search capability that gives AI agents access to tens of billions of documents without requiring external search APIs. The service, now generally available, runs entirely within AWS infrastructure and refreshes its index within minutes of new content appearing online.

Amazon Web Services made its AgentCore harness generally available, reducing production AI agent deployment to two API calls: CreateHarness and InvokeHarness. The managed service handles sandboxed execution, memory, tool integration, and observability, eliminating infrastructure setup for teams building LLM agents.

Amazon Web Services has released new capabilities for Bedrock AgentCore, its platform for building AI agents. The update includes a managed knowledge base that handles vector storage and retrieval across enterprise data sources, native web search using Amazon's Alexa infrastructure, and a payment system enabling agents to access paid content and APIs.

AWS has launched LangChain Deep Agents, an orchestration framework that spawns isolated subagents using Amazon Bedrock AgentCore infrastructure. AgentCore provides dedicated browser MicroVMs running Chromium via Playwright and full Python environments with pre-installed data science libraries, enabling parallel agent execution without context window competition.

Amazon Web Services has launched AgentCore Runtime on Bedrock, providing dedicated Linux microVMs with persistent 14-day storage for coding agents. The service eliminates the need to keep laptops open during agent sessions and supports parallel execution of Claude Code, Codex, Kiro, OpenCode, and other coding agents with isolated environments.

AWS has launched Amazon Bedrock AgentCore, a serverless runtime environment for deploying production AI agents. Turkish fulfillment company OPLOG demonstrated the platform's capabilities by building three business intelligence agents using Anthropic's Claude Sonnet, achieving a 35% reduction in sales cycles and 98% reduction in manual research time.

Amazon Bedrock AgentCore Browser now supports Chrome enterprise policies and custom root CA certificates, giving organizations control over 450+ browser settings for AI agents. The feature enables URL filtering, download restrictions, password manager controls, and connectivity to internal services through custom certificate authorities.

AWS announced Amazon Bedrock AgentCore Payments (preview), enabling AI agents to autonomously discover and pay for APIs, web content, MCP servers, and other agents. Built with Coinbase and Stripe, the service supports micropayments through the x402 protocol with per-session spending limits and full transaction observability.

AWS announced OS Level Actions for Amazon Bedrock AgentCore Browser, extending agent automation beyond the browser's Document Object Model to interact with native operating system UI. The feature enables agents to control system dialogs, security prompts, and context menus through direct mouse and keyboard commands at the OS level.

Amazon Web Services released AgentCore Optimization in preview, introducing an automated performance loop that generates configuration recommendations from production traces, validates them through batch evaluation and A/B testing, and enables continuous agent optimization. The system targets the quality drift problem where AI agents degrade as models evolve and user behavior shifts.

Amazon Bedrock AgentCore Runtime now offers managed session storage to persist agent filesystem state across stop/resume cycles and InvokeAgentRuntimeCommand for executing shell commands directly within agent microVMs. The features address two core challenges in production agent workflows: ephemeral filesystems that reset between sessions and the inability to execute deterministic operations without routing them through LLMs.