All news with #mcp tag

🚀 The CrowdStrike Falcon fall release reframes the platform as an Agentic Security Platform, introducing four core innovations: Enterprise Graph, Charlotte AI AgentWorks, the Agent Collaboration framework (powered by MCP), and an AI-native console. Enterprise Graph unifies telemetry into a real-time, AI-ready data layer to give humans and agents shared context. Charlotte AI AgentWorks delivers a no-code environment to design, test, deploy, and govern mission-specific security agents at scale, while MCP enables secure, orchestrated multi-agent collaboration.

🔒 Security leaders are balancing safe AI adoption with operational gains and focusing on five practical use cases where AI can improve security outcomes. Organizations are connecting LLMs to internal telemetry via standards like MCP, using agents and models such as Claude, Gemini and GPT-4o to automate threat hunting, translate technical metrics for executives, assess vendor and internal risk, and streamline Tier‑1 SOC work. Early deployments report time savings, clearer executive reporting and reduced analyst fatigue, but require robust guardrails, validation and feedback loops to ensure accuracy and trust.

🔗 Azure's Agent Factory blog emphasizes that interoperability is the key to moving agentic AI from isolated prototypes to enterprise-scale solutions. The post promotes open standards like Model Context Protocol (MCP) and Agent2Agent (A2A) to enable shared context, reusable tools, and cross-framework collaboration across runtimes such as Semantic Kernel. It explains how Azure AI Foundry combines these protocols with thousands of connectors, unified observability, and governance so agents can act across SaaS, legacy systems, and custom APIs without costly rewrites.

🔒 AWS Labs published a Model Context Protocol (MCP) server for CloudTrail that enables AI assistants to perform security and compliance analysis via natural‑language queries. The server provides direct access to CloudTrail events and CloudTrail Lake, allowing searches of 90‑day management event histories and Trino SQL queries on Lake data spanning up to 10 years. By exposing these capabilities through a conversational interface, the MCP server removes the need for bespoke API integrations and streamlines investigation and compliance workflows. The component is available in regions that support CloudTrail LookupEvents or CloudTrail Lake and is available with code and documentation in the AWS Labs repository.

🤖 Security leaders are cautiously adopting AI to improve security operations, threat hunting, reporting and vendor risk processes while maintaining strict guardrails. Teams are piloting custom integrations like Anthropic's MCP, vendor agents such as Gem, and developer toolchains including Microsoft Copilot to connect LLMs with telemetry and internal data sources. Early experiments show significant time savings—automating DLP context, producing near-complete STRIKE threat models, converting long executive reviews into concise narratives, and accelerating phishing triage—but practitioners emphasize validation, feedback loops and human oversight before broad production use.

🤖 Amazon Web Services announced enhancements to the Amazon Q Developer chat experience within SageMaker Unified Studio Jupyter notebooks and added a command-line interface for use in notebooks and the Code Editor. By integrating with Model Context Protocol (MCP) servers, the assistant becomes aware of project resources—data, compute, and code—and provides personalized, context-aware help. These updates aim to speed tasks like code refactoring, file edits, and troubleshooting while preserving transparency around assistant actions. The capabilities are available at no additional cost via the Amazon Q Developer Free Tier where SageMaker Unified Studio is offered; customers can enable Amazon Q Developer Pro for expanded functionality.

🔒 Administrators can now manage the Model Context Protocol (MCP) servers used by Amazon Q Developer clients from the AWS console. Admins can enable or disable MCP functionality across their organization; when disabled, users cannot add MCP servers and previously defined servers are not initialized. Q Developer enforces admin settings at session start and every 24 hours. The control covers the CLI and IDE plugins (VSCode, JetBrains, Visual Studio, Eclipse).

🛡️ VirusTotal ran a large-scale audit of 17,845 GitHub projects implementing the MCP (Model Context Protocol) using Code Insight powered by Gemini 2.5 Flash. The automated review initially surfaced an overwhelming number of issues, and a refined prompt focused on intentional malice marked 1,408 repos as likely malicious. Manual checks showed many flagged projects were demos or PoCs, but the analysis still exposed numerous real attack vectors—credential harvesting, remote code execution via exec/subprocess, supply-chain tricks—and recurring insecure practices. The post recommends treating MCP servers like browser extensions: sign and pin versions, sandbox or WASM-isolate them, enforce strict permissions and filter model outputs to remove invisible or malicious content.

🧾 AWS has published an open-source Model Context Protocol (MCP) server for Billing and Cost Management, available in the AWS Labs GitHub repository. The server exposes AWS service APIs and a dedicated SQL-based calculation engine to produce reliable, reproducible cost calculations across large volumes of usage data. It integrates with any MCP-compatible AI assistant or agent — including Q Developer CLI, the Kiro IDE, Visual Studio Code, and Claude Desktop — enabling customers to analyze historical spend, find optimization opportunities, and estimate costs for new workloads with minimal configuration.

🔧 This Microsoft Azure blog post, the second entry in the six-part Agent Factory series, explains how tool ecosystems are defining the next wave of agentic AI. It argues the industry is moving from single-model prompts to extensible platforms that let agents discover and invoke a broad set of capabilities at runtime. The piece highlights the Model Context Protocol (MCP) and Azure AI Foundry for secure, enterprise-grade tool integration, and summarizes five best practices for governance, identity, and observability to achieve scalable, production-ready agents.

🔗 The Harmony SASE MCP Server connects AI and IDE assistants to Harmony SASE, enabling direct, secure access to networking and security context. Built on the open Model Context Protocol (MCP), it exposes a curated set of endpoints so AI tools like Claude, Cursor, and GitHub Copilot can enrich workflows, accelerate investigations, and integrate SASE telemetry into familiar analyst and developer interfaces.