All news with #mcp tag

🛠️ This announcement details the release of the MCP Toolbox Java SDK v1.0, bringing type-safe, enterprise-grade agent orchestration to Java ecosystems. The post outlines new features including a transport abstraction, decoupled authentication, default parameter support, parameter pruning, session tracking, and credential exposure warnings. It illustrates a sample use case (Cymbal Transit) integrating AlloyDB with Spring Boot and LangChain4j to demonstrate conversational state, type-safe tools, and secure production deployment patterns.

🔒 Amazon Bedrock AgentCore Gateway now accepts TLS certificates signed by private certificate authorities for MCP, OpenAPI, and HTTP proxy targets, enabling secure native connections to private endpoints in your VPC without an intermediate Application Load Balancer. You can register PEM-encoded CA certificates stored in Amazon S3 or AWS Secrets Manager, which the gateway uses as a trust anchor for outbound TLS. This support is available in all Regions where AgentCore Gateway and Amazon VPC Lattice are offered. See the AgentCore Developer Guide for details.

🚀 The AWS MCP Server, part of the Agent Toolkit for AWS, is now available in six additional Regions: Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Ireland), Europe (London), and US West (Oregon). The managed Model Context Protocol server provides a single interface for AI coding agents to discover and call AWS services without per-service integrations. Running the server closer to developers reduces latency and helps meet regional data residency requirements. It can access services across all commercial AWS Regions while operating in the listed Regions.

🛠️ The AWS Command Line Interface now includes two new Agent Toolkit commands to simplify skill maintenance. Customers can run aws agent-toolkit check-skill-updates to compare installed skills with registry versions and aws agent-toolkit update-skill --all to update all outdated skills at once. These options reduce manual per-skill checks and streamline keeping agent skills current across domains like storage, networking, and analytics. Ensure you have AWS CLI v2.37.0+ and note availability of the AWS MCP Server in US East (N. Virginia) and Europe (Frankfurt).

🛠️ The Google Cloud CLI remote MCP server is now available in public preview, enabling AI agents to run gcloud and bq commands from a secure, network-isolated execution sandbox. This managed server removes the need to install CLI binaries locally, supports hosted agent platforms, and enforces enterprise-grade controls including zero ambient credentials, IAM-based permissions, Model Armor screening, and Cloud Audit Logging. Agents connect via the MCP standard and authenticate through Agent Identity or OAuth 2.0.

🛠️ Today Google Cloud announces the general availability of Data Agent Kit, a free set of Model Context Protocol (MCP) tools and Google-authored agent skills that let coding agents access and act on Google Cloud data products. The GA release adds support for BigQuery Graph, Bigtable, and Managed Service for Apache Spark in Lakehouse workflows, plus numerous quality-of-life and performance improvements. The kit integrates with IDEs, Antigravity, Claude Code, Codex, Cloud Shell, and Cloud Workstations, enabling agents to inspect schemas, run queries, read job logs, and orchestrate pipelines using customers' IAM permissions.

🤖 Developed jointly by AWS and OpenAI, Bedrock Managed Agents (BMA) is an AWS-native implementation of OpenAI's Agents API that runs entirely inside AWS. BMA maintains state through durable sessions, manages tool selection and execution, and allows reusable skills and MCP-connected tools. Each agent uses its own IAM role, supports human approvals for consequential actions, and logs supported API activity to AWS CloudTrail. The preview is available in select US regions with no additional BMA charge beyond consumed AWS resources.

🔒 The official MCP Python SDK had a vulnerability that allowed a malicious MCP server to trick clients into sending OAuth credentials to an attacker-controlled token endpoint. Affected releases exposed the client secret, authorization code, and PKCE proof key; fixes were released in versions 1.30.0 and 2.2.0. The issue impacts clients using specific OAuth providers over HTTP and requires upgrades plus configuration changes to fully mitigate.

🛡️ New research from Ox Security warns that Model Context Protocol (MCP) servers are creating an enterprise governance gap as AI adoption grows. MCP standardizes connections between AI models and external tools or data, but in doing so can bypass residency controls, zero trust boundaries and granular IAM policies. Analysis of public registries found many hosts outside the US and some unregistered, while permission models like “always-allow” enabled unauthorized data access in tested scenarios.

🧭 Anthropic has launched the public Claude Marketplace, aggregating plugins, connectors, agents, and partner products in one location. The marketplace already lists more than 2,000 offerings from vendors including Atlassian, Google, Microsoft, Notion, and Salesforce. Companies can also buy Claude-powered agents and services from partners such as CrowdStrike, Snowflake, and consulting firms like Accenture and Deloitte. Developers can publish connectors and plugins using MCP and Agent Skills to reach Claude customers.

🛠️ AWS End User Messaging and Amazon SES now expose AI agent skills for the AWS MCP Server so developers can perform messaging tasks using natural-language prompts. The skills provide validated, step-by-step guidance for actions like verifying sending identities, creating branded RCS agents, and sending production emails. They integrate with popular AI coding agents such as Claude Code, Codex, Cursor, and Kiro, and are installed via the aws-core plugin or MCP configuration. Installation and per-skill details are covered in the respective agent setup guides.

🤖 AWS announced general availability of the AWS Marketplace metering agent skill, an AI-guided assistant that helps sellers build, deploy, and validate usage-based SaaS metering integrations from within their AI coding assistant. The skill collects product details, recommends APIs, generates integration code and a tailored CloudFormation stack, and runs end-to-end tests against AWS Marketplace. It supports validation, guardrails, a serverless metering pipeline, Concurrent Agreements, and debugging tools, and is available via the AWS MCP Server to MCP-compatible AI coding assistants with no plugin installation required.

🔎 Lucius AI, a tender-intelligence startup covering five continents, consolidated its relational catalog, audit logs, and vector embeddings into AlloyDB for PostgreSQL and automated routine operations via the Model Context Protocol (MCP). By migrating semantic search to a ScaNN index, query latency fell from 1.14s to 24ms, a 47x improvement. The platform ingests notices from multiple procurement sources and runs across two production regions with strict least-privilege controls.

🚀 Today Google Cloud announced a new installable plugin for AI coding agents that packages related agent skills and tools to simplify working with Google Cloud. The plugin follows the open Agent Plugins specification to provide consistent manifests and interoperability across agent environments. The flagship google-cloud-developer plugin helps agents with authentication, authorization, project management, gcloud guardrails, and integrates the Developer Knowledge MCP server for up-to-date documentation grounding.

🧭 The Data Agent Kit streamlines exploratory data investigations by enabling agents inside IDEs to query multiple systems—data warehouses, operational databases, and object stores—via the open Model Context Protocol (MCP) and modular skills. It integrates with popular IDEs and plugins so developers can run queries, inspect execution trails, and grant scoped permissions without switching tools. The kit can convert ad-hoc analysis into reproducible dbt projects and iteratively fix issues, though human oversight and data quality checks remain important.

🛠️ The AWS Model Context Protocol Server (AWS MCP Server) now supports a serverless capability enabling coding agents like Claude Code and Kiro to diagnose AWS Lambda functions and connected resources. The capability lets agents inspect Lambda, Amazon API Gateway, EventBridge, S3, DynamoDB, SNS, SQS, and Step Functions, correlate errors against a 7-day baseline, surface recurring errors, retrieve deployed configurations, provide change timelines, and analyze latency. It reduces token usage by aggregating comprehensive data in a single call. The MCP Server is available via the Agent Toolkit for AWS or as a standalone installation and can access services in all commercial AWS Regions while running in US East (N. Virginia) and Europe (Frankfurt).

🔧Amazon Quick now offers enhanced connector controls and Model Context Protocol (MCP) synchronization for connectors. Admins and connector owners can selectively enable or disable individual tools within a connector and configure tool permission settings to require consent or delegate decisions to end users. MCP sync ensures connectors stay up to date as external MCP servers add or modify tools and metadata. These updates are available in all Regions where Amazon Quick is offered.

🔗 Amazon Quick now integrates with the AWS Agent Registry to let users discover, enable, and share MCP servers and agents directly within their Amazon Quick workspace. Connection details are pre-populated from the registry, enabling quick enablement and distribution for chat, agents, apps, flows, and research. The integration is available in all regions where Amazon Quick and Amazon Bedrock AgentCore are supported, and administrators can connect via Manage account > Permissions > AWS Agent Registry.

🔧 Amazon Redshift integrates with the Agent Toolkit for AWS to let AI agents like Claude Code, Kiro, and Cursor build, query, troubleshoot, and migrate Redshift data warehouses and data lakes. The integration pairs the AWS MCP (Model Context Protocol) server for authenticated AWS API execution with curated Redshift skills—packages of procedures and reference material—to reduce query errors and streamline common tasks. Skills cover SQL syntax, metadata discovery, data loading, materialized view best practices, function and type guidance, extensions, and end-to-end migration workflows for both provisioned clusters and Serverless workgroups. The capability requires no infrastructure changes, is available at no extra charge in supported Regions, and can be enabled via the aws-data-analytics plugin or discovered at runtime by agents with MCP access.

🔒 Gemini Enterprise for Financial Services integrates Google’s agentic AI into capital markets and corporate banking workflows with secure, auditable connectors and purpose-built financial skills. It ships with a Google-managed Financial Research agent, MCP connectors to licensed market and enterprise data, and an ecosystem of partner agents and integrators. A governed control plane enforces policies, private data isolation, and verifiable citations for outputs.