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The WebMCP Early Preview is underway → Expose structured data to AI agents defining your capabilities as tools so they no longer have to scrape screens or burn through valuable tokens.

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Chrome for Developers

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31,277 просмотров • 3 месяцев назад •via X (Twitter)

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It can be challenging for AI agents to solve complex user intents by synthesizing signals like screenshots, the DOM, and the Accessibility Tree. Enter WebMCP, a proposed web standard that aims to expose structured tools for AI agents directly on existing websites, now in origin trial ⬇️
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It can be challenging for AI agents to solve complex user intents by synthesizing signals like screenshots, the DOM, and the Accessibility Tree. Enter WebMCP, a proposed web standard that aims to expose structured tools for AI agents directly on existing websites, now in origin trial ⬇️

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🤖 Make your website agent-ready with WebMCP, the new protocol for reliable, structured AI → Join André Bandarra and Francois Beaufort on WeAreDevelopers as they dive into how WebMCP moves the web beyond human-only UI to high-performance agent architecture.

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Data at internet scale means little when the data is unreliable or fake. Turing laureate and Ethernet inventor Bob Metcalfe points to this defining problem in the age of AI. Agents need shared verifiable memory so the knowledge behind their actions can be traced and checked before they act. 🕸️

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"Agents can only go so far without the data and apps. And this is where Salesforce wins with AI. The data is more important than ever. Or your agents just can't perform at the level of accuracy We need them to." Marc Benioff
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Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.
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Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.

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$swarms LaunchPad is officially in beta 🤖🤖🤖 You can effortlessly tokenize your agents, generate revenue from them, and earn $swarms tokens as rewards for providing valuable agents to the market. Get started below ⬇️
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Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

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Today we're launching Airbyte Agents. It’s a platform meant to solve what we call the discovery gap. Agents in demos are successful because they know the fields and sources they have to call to solve their task. Agents in production fail because they don’t have that knowledge assembled beforehand. Airbyte Agents, powered by the Context Store, fixes that with one unified layer of pre-materialized context across all of your business systems. Real results. 80% fewer tokens. 40% fewer tool calls. Get more out of your AI tool’s plan limit. Three ways to build: MCP, SDK, or no-code Automations 💡 We're early, and we want to build with our users. Try Airbyte Agents today.

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“The currency for AI is crypto.” ~CZ Humans generate 300 trillion tokens a day. Soon, AI will generate 10× that. As AI begins trading with AI, and blockchain secures data and payments, productivity decouples from population. CZ predicts GDP may no longer be tied to people.

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The Skillful AI platform is now live The place where you can unleash the true power of AI and let your creativity run free 🤖 Get 3X the performance by making up to 3 different LLMs work together for your needs 🤖 Create your custom personalities for the AI agents as detailed as you can dream of, then bring them to life on telegram, discord, or monetize them in our AI marketplace 🤖 Feed your Agents specific knowledge and keep it fully private through 's blind computing technology 🤖 Plug your AI into everything with our Skills and Integrations: From social media like X & Telegram, to agents launching their own tokens via @pumpdotfun, trading tokens on Solana to even making your own AI NPC characters for your games through our SDKs ✅ We’ve got a ton of exciting extra features coming to the platform very soon. We are committed to bringing you the ultimate AI ecosystem 🥂 Ps: Have questions about the platform? Drop a ticket in our Discord, and we’ll be happy to assist 🫡 🌐

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Sharing is caring. Assist your loved ones when they have no available data bundles by sharing yours with them. Simply go to to add up to 5 beneficiaries of your data or directly request your people to share data with you.
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Sharing is caring. Assist your loved ones when they have no available data bundles by sharing yours with them. Simply go to to add up to 5 beneficiaries of your data or directly request your people to share data with you.

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Today we are launching Mireye (YCS26) with Y Combinator The easiest way to build agentic applications for the physical world. AI agents are starting to act in the real world, but they can't reliably understand it. Mireye is one API and MCP that connects agents to the physical world: data, enrichment, tools, and signals that power them to make decisions. One line of code to make your agents street smart.

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