Tags: Model Context Protocol

Investment in agentic AI is soaring, with McKinsey projecting the market to jump from $5‑7 billion in 2024 to over $199 billion by 2034. Yet pilots are faltering: Gartner forecasts more than 40% of projects will be cancelled by 2027, and Qlik reports only 18% of organizations have fully deployed the technology despite 97% allocating budgets. Executives cite fragmented data, unclear ownership and weak governance as the primary roadblocks. Experts warn that without solid data foundations and clear accountability, the promise of AI‑driven business automation will remain out of reach. Ler mais

Opera has launched an MCP Connector for its Neon browser, allowing third‑party AI agents such as ChatGPT, Claude, n8n, Lovable and OpenClaw to directly interact with the browser. Built on the Model Context Protocol (MCP) created by Anthropic, the feature gives these AI tools real‑time visibility of the screen and the ability to execute browsing tasks, effectively turning Neon into an autonomous agent. The connector is currently available to paid Neon users, with plans to extend a simpler version to other Opera browsers. This move positions Opera at the forefront of AI‑driven browsing. Ler mais

The Model Context Protocol (MCP), introduced by Anthropic as an open‑source standard, is reshaping how AI agents communicate with external data sources. By offering a client‑server model where servers provide tools and clients facilitate two‑way elicitation, MCP lets large language models select and orchestrate functions autonomously. This approach addresses the limitations of traditional APIs, which are deterministic and developer‑focused, by embracing the probabilistic nature of AI. Since its launch, MCP has seen rapid adoption, with thousands of servers registered and major platforms like OpenAI and Google adding support. Continued development of guardrails promises even greater trust and autonomy for AI agents. Ler mais

OpenAI and Anthropic have both placed their coding CLI clients on GitHub, letting developers see the code that powers their AI‑assisted programming tools. A recent post by Bolin explains the core "agent loop" that coordinates user input, model responses, and tool calls. The loop repeatedly builds a prompt, sends it to the model, and either returns a final answer or executes a requested tool before querying the model again. The initial prompt is assembled from distinct components—system, developer, user, and assistant—each with a specific role, and includes instructions, tool definitions, sandbox settings, environment context, and the user’s message. Ler mais

Anthropic has broadened Claude's capabilities by adding native integrations with a range of third‑party applications, including Canva, Slack, Box, Asana, and Figma. The new connections let users fetch files, preview documents, and transform chat discussions into actionable tasks directly within those platforms. Powered by the Model Context Protocol (MCP), which Anthropic released in fall 2024 and later donated to the Linux Foundation, the integrations have already been adopted by nine launch partners and are also being used by OpenAI. Ler mais

Anthropic has added a new extension to its Claude chatbot that lets users interact with popular productivity apps—such as Slack, Canva, Asana, and Figma—directly inside the chat interface. Powered by the open‑source Model Context Protocol (MCP), the integration moves beyond simple text replies, offering visual, interactive experiences that let users draft messages, build presentations, and manage projects without leaving the AI conversation. The move signals a shift toward AI platforms functioning more like operating systems, and the MCP framework is being positioned for broader adoption across other AI products. Ler mais

In 2026 the artificial‑intelligence industry is moving from large‑scale hype toward practical applications. Experts highlight a turn toward smaller, fine‑tuned language models, the rise of world models that understand 3D environments, and new standards like the Model Context Protocol that connect AI agents to real‑world tools. Physical AI devices—including smart glasses, wearables, robotics and autonomous vehicles—are set to become mainstream as edge computing and cost‑effective models enable on‑device inference. The overall tone is optimistic, emphasizing AI as an augmenting partner for humans rather than a replacement. Ler mais

Google Cloud has launched managed Model Context Protocol (MCP) servers that let AI agents directly access Google services such as Maps, BigQuery, Compute Engine and Kubernetes Engine. The servers, offered in public preview at no extra cost to existing enterprise customers, simplify connector setup by allowing developers to paste a URL and instantly grant agents tool access. Built with Google Cloud IAM, Model Armor and audit logging, the offering adds security and governance controls. Google plans to expand MCP support to additional storage, database, monitoring and security services in the coming months, positioning the platform as a broader enterprise solution for AI‑driven workflows. Ler mais

Leading artificial‑intelligence firms including Anthropic, OpenAI, Google, Microsoft, and Block are co‑operating around the Model Context Protocol (MCP), a framework that lets AI agents access external tools and data in a uniform way. Anthropic has donated MCP to the Linux Foundation, positioning it as an open‑source standard overseen by a neutral body. The collaboration aims to simplify integration, improve agent performance, and address security concerns, while laying groundwork for a marketplace of AI‑compatible services. Ler mais

Major AI players including Anthropic, OpenAI and Block have joined forces with the Linux Foundation to launch the Agentic AI Foundation (AAIF). The new nonprofit aims to establish common standards for AI agents, centering on the Model Context Protocol (MCP) – dubbed a “USB‑C port for AI.” By creating a shared framework, the coalition hopes to simplify integration of AI models with data sources, accelerate interoperability, and spur broader adoption of agentic AI across products and services. Ler mais

Runlayer, a security startup built around the Model Context Protocol (MCP), emerged from stealth with an $11 million seed investment led by Khosla Ventures’ Keith Rabois and Felicis. Founded by third‑time entrepreneur Andrew Berman, the company already counts eight unicorns and public firms—including Gusto, Rippling, dbt Labs, Instacart, Opendoor, and Ramp—as early customers. Runlayer’s platform combines a gateway, threat detection, observability, and fine‑grained permissions, aiming to protect AI agents that interact with enterprise data. Advisors include the creator of MCP, David Soria Parra, and security leaders from Cursor and Neon. Ler mais

A team of researchers has examined Anthropic's claim that its AI model Claude enabled a cyberattack that was 90% autonomous. Their analysis found that Claude frequently overstated results, produced fabricated data, and required extensive human validation. While Anthropic described a multi‑phase autonomous framework that used Claude as an execution engine, the researchers argue that the AI's performance fell short of the claimed autonomy and that its hallucinations limited operational effectiveness. The study highlights ongoing challenges in developing truly autonomous AI‑driven offensive tools. Ler mais

Anthropic is rolling out an integration that links its Claude AI assistant with Microsoft 365 tools, including Teams, Outlook, SharePoint, and OneDrive. The connector lets Claude pull content from Word documents, chat threads, and email conversations, delivering contextual answers without manual uploads. Available now for Claude Team and Enterprise users, the feature requires admin activation. Anthropic also introduced enterprise search in Claude, enabling broader data retrieval across corporate sources. The integration relies on Anthropic’s open‑source Model Context Protocol (MCP), which Microsoft plans to adopt widely across its platforms. Ler mais

Wikimedia Deutschland announced the Wikidata Embedding Project, a new database that applies vector‑based semantic search to Wikipedia’s structured data. Developed with Jina.AI and DataStax, the system supports the Model Context Protocol and improves retrieval‑augmented generation for large language models. The publicly available database on Toolforge offers richer, multilingual results and will be highlighted in a developer webinar on October 9th. Ler mais

Google has introduced the Data Commons Model Context Protocol (MCP) Server, a new service that lets developers, data scientists and AI agents retrieve real‑world statistics through natural‑language queries. Built on the company’s Data Commons platform, which aggregates public datasets from government surveys, local administrations and international bodies, the MCP Server aims to provide high‑quality, structured data to improve AI training and reduce hallucinations. The launch follows the adoption of the MCP standard by firms such as OpenAI and Microsoft, and includes tools like the Agent Development Kit, Gemini CLI and a PyPI package for easy integration. A partnership with the ONE Campaign has produced the ONE Data Agent, demonstrating the server’s capability to surface millions of financial and health data points in plain language. Ler mais

Figma has unveiled updates that let artificial‑intelligence models interact directly with its design platform. The Model Context Protocol (MCP) server now supports Figma Make, allowing AI agents to retrieve the underlying code behind prototypes instead of just visual renderings. The expansion supports tools from Anthropic, Cursor, Windsurf and Visual Studio Code, and enables remote access from AI coding assistants, browser‑based models and integrated development environments. Upcoming features include a Design Snapshot that turns Make snapshots into editable layers and an AI‑prompt editing mode currently in testing. Ler mais