Mcp

Google quietly published something very useful on GitHub in early March: gws, a command-line interface for the full Google Workspace API surface. It ships with 100+ pre-built agent skills covering Gmail, Drive, Docs, Calendar, and Chat — and it includes a built-in MCP server that lets AI clients like Claude Desktop, Gemini CLI, and VS Code access your Workspace directly. This is the thing that used to require a custom OAuth flow, API client library setup, and a day of plumbing. Now it’s a CLI install and a config file. ...

Something genuinely important is shipping in Chrome 146: an early preview of WebMCP, a W3C draft standard jointly developed by Google and Microsoft that fundamentally changes how AI agents interact with websites. Right now, AI agents that browse the web do so by scraping DOM elements — reading HTML, finding buttons, inferring what actions are available. It’s brittle. A website redesign breaks the agent. A modal renders differently across browsers and the agent gets stuck. This approach works well enough for demos but fails at production scale. ...

If you’ve deployed OpenClaw agents with MCP server integrations, there’s a good chance your agents have more access than you realize — and your audit logs are hiding it. Security researchers call it the “god key” problem, and it’s a genuine architectural gap in how most teams are running MCP today. Here’s what it is, why it matters, and how to fix it. What Is the MCP God Key Problem? Model Context Protocol (MCP) servers act as bridges between your AI agents and external tools — databases, file systems, APIs, SaaS platforms. The problem is how credentials flow through that bridge. ...

Nearly 70% of enterprises are already running AI agents in production. Another 23% plan to deploy them in 2026. And the vast majority of those agents are operating with no audit trail, no identity governance, and full access to the data they touch. Security analysts have a name for this: identity dark matter. The term comes from a Hacker News analysis published this week, and it’s earning traction because it captures something real. Like cosmological dark matter, AI agent identities exert enormous gravitational force on the systems around them — they make decisions, consume data, trigger actions — while remaining largely invisible to the tools and processes organizations use to manage access and risk. ...

Apple just crossed a line no major OS vendor had crossed before. With today’s release of Xcode 26.3, the company has shipped native, first-class support for autonomous AI coding agents — plugging Anthropic’s Claude and OpenAI’s Codex directly into the IDE via the Model Context Protocol (MCP). This is not a copilot autocomplete feature. These are full agents. What Xcode 26.3 Actually Does The new agent integration lets Claude and Codex do the kind of work a junior developer might spend a full morning on — autonomously. Here’s what agents can do inside Xcode 26.3: ...

Enterprise data infrastructure and agentic AI are colliding in a significant way today. Confluent — the company built around Apache Kafka and real-time streaming data — has added official support for the Agent2Agent (A2A) protocol to its Confluent Intelligence platform. Alongside MCP (Anthropic’s Model Context Protocol), A2A is now a first-class citizen in Confluent’s agent orchestration layer. This is a story about infrastructure maturing to meet where agents are going — and it matters for any team building multi-agent systems on top of real-world data streams. ...

Twilio Launches A2H: Open Protocol to Standardize Agent-to-Human Workflows One of the most underrated problems in production agentic AI systems isn’t the AI — it’s the handoff. When does an agent escalate to a human? How does a human authorize a sensitive action? Who keeps the audit trail? These questions don’t have good answers yet, and most teams are solving them ad-hoc with a patchwork of webhooks, Slack bots, and prayers. ...