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I'm excited that Visual Studio Code (Insiders) now supports the full Model Context Protocol (MCP) spec, including sampling! ⚡ I just published a new blog post and video showing how you can use sampling to generate tags for journal entries in an MCP-powered app. Check out what’s possible!

189,564 görüntüleme • 1 yıl önce •via X (Twitter)

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Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

Read more here: Join me for my MCP Fundamentals workshop where we'll actually use this feature!

Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

More on this here:

PDF GPT profil fotoğrafı
PDF GPT2 yıl önce

This is my favorite AI tool for reviewing reports. Just upload a report, ask for a summary, and get one in seconds. It's like ChatGPT, but built for documents. Try it for free.

Babacar C. DIA profil fotoğrafı
Babacar C. DIA1 yıl önce

@code the lighting looks great!

Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

@code Thanks 😊

Ian Maurer 🧬🤖🐍 profil fotoğrafı
Ian Maurer 🧬🤖🐍1 yıl önce

@code Keep it up Kent, love the MCP content.

Catalin Miron - AnimateReactNative.com profil fotoğrafı
Catalin Miron - AnimateReactNative.com1 yıl önce

@code I really like this setup!

Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

@code Thanks!

Gabriel from Kodus profil fotoğrafı
Gabriel from Kodus1 yıl önce

@code Awesome stuff → but seriously, WTF is that VSCode font theme?!

Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

@code

Michael Grinich profil fotoğrafı
Michael Grinich1 yıl önce

@code sampling is such a powerful and under discussed feature!

Kent C. Dodds ⚡ profil fotoğrafı
Kent C. Dodds ⚡1 yıl önce

@code It's under discussed because until now nobody could use it 😅

Benzer Videolar

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!

Andrew Ng

142,234 görüntüleme • 1 yıl önce