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🔴 MCP Live is tomorrow! Join us at 9 AM PT with experts from Microsoft, GitHub, Anthropic, Okta, Prefect, and Amazon to explore what’s new across the MCP ecosystem.

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MCP servers were stuck on text and data. Not anymore. 👀 Proposed by Anthropic, OpenAI, and the MCP-UI community, the new MCP Apps Extension standardizes interactive interfaces with security built in. Here's what you need to know. ▶️
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MCP servers were stuck on text and data. Not anymore. 👀 Proposed by Anthropic, OpenAI, and the MCP-UI community, the new MCP Apps Extension standardizes interactive interfaces with security built in. Here's what you need to know. ▶️

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Microsoft is moving FAST. You can now vibe code with GitHub Copilot. They're rolling our Agent mode and MCP support to all VS Code users
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Microsoft is moving FAST. You can now vibe code with GitHub Copilot. They're rolling our Agent mode and MCP support to all VS Code users

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It's never been easier to get pwned combining Cursor auto-run + Anthropic MCP Here is a POC using an external MCP server that parses GitHub repositories documentations turning into RCE. There are 0 AI Guardrails when asking Cursor to follow instructions coming from MCP🙃
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It's never been easier to get pwned combining Cursor auto-run + Anthropic MCP Here is a POC using an external MCP server that parses GitHub repositories documentations turning into RCE. There are 0 AI Guardrails when asking Cursor to follow instructions coming from MCP🙃

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WE WON THE ANTHROPIC MCP HACKATHON! (in the nyc enterprise category) We knew Fortune 500s want MCP but need an Enterprise AI™ solution. So we built a Claude MCP client in Slack was SOC II Type 7, ISO 32456 and Microsoft Certified® Finally MCP is ready for the big leagues!
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WE WON THE ANTHROPIC MCP HACKATHON! (in the nyc enterprise category) We knew Fortune 500s want MCP but need an Enterprise AI™ solution. So we built a Claude MCP client in Slack was SOC II Type 7, ISO 32456 and Microsoft Certified® Finally MCP is ready for the big leagues!

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New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!
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New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

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Running final scripts. Environment looks good. ✅ Microsoft Build has officially arrived in Seattle, join us live for the opening keynote tomorrow, May 19th, at 9:05am PT:
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Running final scripts. Environment looks good. ✅ Microsoft Build has officially arrived in Seattle, join us live for the opening keynote tomorrow, May 19th, at 9:05am PT:

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New week, new Alpha Series episode! Join us tomorrow at 1pm UTC to dive into how AI is shaping the future of Web3 with experts from Autonomys | AI3.0 , PlayFi (visit us at @LiftDataAI), and Kiva AI!
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New week, new Alpha Series episode! Join us tomorrow at 1pm UTC to dive into how AI is shaping the future of Web3 with experts from Autonomys | AI3.0 , PlayFi (visit us at @LiftDataAI), and Kiva AI!

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🚨Breaking: Microsoft just dropped major updates - GitHub now has Copilot Agent Mode - MCP support rolling out to all VS Code users - New GitHub Copilot Pro+ Plan Vibe coding with GitHub Copilot. 1/3 🧵 Video Source : GitHub YT
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🚨Breaking: Microsoft just dropped major updates - GitHub now has Copilot Agent Mode - MCP support rolling out to all VS Code users - New GitHub Copilot Pro+ Plan Vibe coding with GitHub Copilot. 1/3 🧵 Video Source : GitHub YT

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Unlock smarter, more dynamic workflows with AI tools like GitHub Copilot. 🦾 Here's how to set up the new Remote GitHub MCP Server. ⬇️
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Unlock smarter, more dynamic workflows with AI tools like GitHub Copilot. 🦾 Here's how to set up the new Remote GitHub MCP Server. ⬇️

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Anthropic released interactive apps for Claude. Interactive apps can respond with interactive UI Widgets to enable additional usecases. "MCP Apps is a new extension to MCP that lets any MCP server deliver an interactive interface within any supporting AI product"
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Anthropic released interactive apps for Claude. Interactive apps can respond with interactive UI Widgets to enable additional usecases. "MCP Apps is a new extension to MCP that lets any MCP server deliver an interactive interface within any supporting AI product"

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Introducing GoPlus-MCP. The first AI-native security layer for Web3. Now natively callable from Anthropic Claude, DeepSeek, and other LLM clients supporting MCP. A new way of thinking about Web3 security. Try it now at

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Microsoft CTO Kevin Scott says MCP is becoming the HTTP of the agentic web. Like HTTP, it's lightweight, composable, and interoperable. Microsoft is betting on MCP as the backbone for agent communication, scale, and evolution.
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Microsoft CTO Kevin Scott says MCP is becoming the HTTP of the agentic web. Like HTTP, it's lightweight, composable, and interoperable. Microsoft is betting on MCP as the backbone for agent communication, scale, and evolution.

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Anthropic engineer: "At Anthropic, 85% of our engineers building agentic Loops and Graphs powered by MCP Loops + Graphs + MCP - that's how the self-learning agentic system looks like" in a 30-minute workshop, the Anthropic engineer who created MCP reveals how to build a self-learning agentic system Worth more than a $500 agentic course on the internet Watch the masterclass, then read how to build self-learning agents with MCP in the article below

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