Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Deciding between A2UI and MCP Apps for your agentic interfaces? You don't have to choose 💫 This guide breaks down 3 architectural patterns for combining the best of declarative and custom UIs, including how A2UI and MCP Apps can seamlessly interact with each other.

FlutterDev's profile picture

Flutter

277,632 subscribers

20,101 görüntüleme • 26 gün önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

OpenAI just dropped the Apps SDK, built on MCP. This is the future of how users will interact with your apps. You won’t need to build a chatbot anymore. OpenAI is the chatbot. You just expose your tools through MCP. Exciting progress toward Jarvis!
9:03

OpenAI just dropped the Apps SDK, built on MCP. This is the future of how users will interact with your apps. You won’t need to build a chatbot anymore. OpenAI is the chatbot. You just expose your tools through MCP. Exciting progress toward Jarvis!

Kent C. Dodds 🏹

152,179 görüntüleme • 9 ay önce

Introducing SperaxOS Plugin Store Browse & install plugins right from the chat. Choose from many of your favorite apps, plugins, and tools or bring your own custom MCP Servers. Watch how anyone can import any MCP Server into SperaxOS chat in under 1 minute.
1:00

Introducing SperaxOS Plugin Store Browse & install plugins right from the chat. Choose from many of your favorite apps, plugins, and tools or bring your own custom MCP Servers. Watch how anyone can import any MCP Server into SperaxOS chat in under 1 minute.

Sperax | SperaxOS

22,924 görüntüleme • 4 ay önce

Using Cursor and Supabase allows us to build apps in record time! In this video guide, I will explain how to use Cursor agent, MCP, Supabase CLI, and other techniques to build apps more efficiently! Watch the full video guide here 👇
44:57

Using Cursor and Supabase allows us to build apps in record time! In this video guide, I will explain how to use Cursor agent, MCP, Supabase CLI, and other techniques to build apps more efficiently! Watch the full video guide here 👇

Tyler Shukert

89,371 görüntüleme • 1 yıl önce

I've been waiting for this. The Unified MCP is here! Rube is a universal MCP server to connect your AI agents to all *your* apps. Works with your favorite IDE, Claude Code, and other MCP clients. Watch it research YouTube vids → generate a full content strategy doc. Insane!
1:55

I've been waiting for this. The Unified MCP is here! Rube is a universal MCP server to connect your AI agents to all *your* apps. Works with your favorite IDE, Claude Code, and other MCP clients. Watch it research YouTube vids → generate a full content strategy doc. Insane!

elvis

62,262 görüntüleme • 11 ay önce

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!
2:43

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

142,010 görüntüleme • 1 yıl önce

Comment “MCP” and I’ll DM you the servers I use every day Browser MCP tests apps for you, Magic MCP builds UI in seconds, and GitMCP links your AI to any repo. These are only 3 of the seven MCPs I use. Once you try them, you’ll never want to build with AI without them.
0:48

Comment “MCP” and I’ll DM you the servers I use every day Browser MCP tests apps for you, Magic MCP builds UI in seconds, and GitMCP links your AI to any repo. These are only 3 of the seven MCPs I use. Once you try them, you’ll never want to build with AI without them.

Prajwal Tomar

19,085 görüntüleme • 10 ay önce

Don't know what is MCP and want to get a very quick intro lesson without the hype? I've got you covered MCP clients (like Claude, Cursor) are like the Android Phones and MCP Servers are like Android Apps. You can install them on your client and give it new capabilities!
2:11

Don't know what is MCP and want to get a very quick intro lesson without the hype? I've got you covered MCP clients (like Claude, Cursor) are like the Android Phones and MCP Servers are like Android Apps. You can install them on your client and give it new capabilities!

Shobhit Bakliwal

14,128 görüntüleme • 1 yıl önce

You can now run apps within powered by MCP Apps. Analyze data, edit tickets, draft messages, generate diagrams and more with Claude's interactive connectors. Grateful to our team, the open source community, and our partners for this launch 🚀
0:31

You can now run apps within powered by MCP Apps. Analyze data, edit tickets, draft messages, generate diagrams and more with Claude's interactive connectors. Grateful to our team, the open source community, and our partners for this launch 🚀

Sean Strong

132,465 görüntüleme • 6 ay önce

Introducing the Developer’s Guide to AI Agent Protocols. Stop writing custom integration glue for every tool, API, and frontend. We used Google Agent Development Kit to build a B2B agent that handles the full stack using 6 open standards: MCP, A2A, UCP, AP2, A2UI, and AG-UI The future of agents is interoperable. Read the full technical guide here:
0:35

Introducing the Developer’s Guide to AI Agent Protocols. Stop writing custom integration glue for every tool, API, and frontend. We used Google Agent Development Kit to build a B2B agent that handles the full stack using 6 open standards: MCP, A2A, UCP, AP2, A2UI, and AG-UI The future of agents is interoperable. Read the full technical guide here:

Google for Developers

116,721 görüntüleme • 4 ay önce

Base MCP scales what agents can achieve onchain Your agent can prepare transfers, swaps, lending, and borrowing across top apps on Base With every transaction approved by you Bringing the ecosystem into the agentic economy
0:50

Base MCP scales what agents can achieve onchain Your agent can prepare transfers, swaps, lending, and borrowing across top apps on Base With every transaction approved by you Bringing the ecosystem into the agentic economy

Base

71,611 görüntüleme • 1 ay önce

In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:
1:09

In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:

DeepLearning.AI

23,829 görüntüleme • 1 yıl önce

most people don’t know the difference between MCP and agentic skills. this 20mins course teaches you everything you need to know. it’s free on YT. bookmark. watch. at the end of the video course, you’d have learnt what the differences and similarities between agents skill and MCP. and the best part when to use which. this is just the first 12mins, check the cs for link to the full video.
12:27

most people don’t know the difference between MCP and agentic skills. this 20mins course teaches you everything you need to know. it’s free on YT. bookmark. watch. at the end of the video course, you’d have learnt what the differences and similarities between agents skill and MCP. and the best part when to use which. this is just the first 12mins, check the cs for link to the full video.

m0h

69,625 görüntüleme • 2 ay önce

Meet Tempo's MCP App Store 👋 Seamlessly integrate your web and mobile apps with Stripe, OpenAI, , Exa, Google Gemini & 40+ more integrations Built on MCP using Supabase — let AI handle the complexity You focus on product Here's how it works 👇 1/5 🧵
0:47

Meet Tempo's MCP App Store 👋 Seamlessly integrate your web and mobile apps with Stripe, OpenAI, , Exa, Google Gemini & 40+ more integrations Built on MCP using Supabase — let AI handle the complexity You focus on product Here's how it works 👇 1/5 🧵

Tempo (YC S23)

78,601 görüntüleme • 1 yıl önce

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:
3:08

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,315 görüntüleme • 9 ay önce

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.
0:52

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.

Carlos Mendez

188,280 görüntüleme • 7 ay önce

RIP traditional prompt engineering platforms. Meet Adaline Ai the single platform where you can write, test, and ship the best prompts for your AI Agents, MCP, RAG, and LLM apps. One platform. Zero hassle. Step-by-step tutorial :
0:37

RIP traditional prompt engineering platforms. Meet Adaline Ai the single platform where you can write, test, and ship the best prompts for your AI Agents, MCP, RAG, and LLM apps. One platform. Zero hassle. Step-by-step tutorial :

Parul Gautam

43,009 görüntüleme • 1 yıl önce

Introducing the A2UI Widget Builder ⚙️ An interactive demo and template to build A2UI Widgets and bring them into your application. Powered by CopilotKit & Google's new A2UI spec Includes... - Widget Gallery: premade UI widgets you can use & modify - Material Icons: 100 of the most commonly used icons - UI Components: common components preview, usage and props - Source code and data on any widget/icon/component - Built with CopilotKit- so you get chat UI, generative UI, etc. Try it out: Tutorial of how to get started: Repo:
0:30

Introducing the A2UI Widget Builder ⚙️ An interactive demo and template to build A2UI Widgets and bring them into your application. Powered by CopilotKit & Google's new A2UI spec Includes... - Widget Gallery: premade UI widgets you can use & modify - Material Icons: 100 of the most commonly used icons - UI Components: common components preview, usage and props - Source code and data on any widget/icon/component - Built with CopilotKit- so you get chat UI, generative UI, etc. Try it out: Tutorial of how to get started: Repo:

CopilotKit🪁

18,510 görüntüleme • 7 ay önce

Learn how to build GPT-3 AI apps with OpenAI and @Vercel edge functions. In this video, I explain how I built and how you can build your own GPT-3 powered apps:
6:18

Learn how to build GPT-3 AI apps with OpenAI and @Vercel edge functions. In this video, I explain how I built and how you can build your own GPT-3 powered apps:

Hassan

222,270 görüntüleme • 3 yıl önce

Here's your guide to discover the best apps for staying organized, ordering groceries, and even predicting the weather! 📱 Tap into the USA's top apps of 2023. 📲:
0:36

Here's your guide to discover the best apps for staying organized, ordering groceries, and even predicting the weather! 📱 Tap into the USA's top apps of 2023. 📲:

App Store

28,617 görüntüleme • 2 yıl önce