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ICP MCP making games on Internet Computer a reality...?! DFINITY Foundation's Model Context Protocol (MCP), a standard introduced to let AI models connect securely to external data and tools, is already being put to good use. A new post shares X2 using Anthropic's Claude to play a generated video...

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wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.
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wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

Molly O’Shea

20,408 просмотров • 1 год назад

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 просмотров • 1 год назад

Explore the dart_mcp package, a powerful framework for building Model Context Protocol (MCP) servers and clients in Dart, enabling you to connect AI models to resources, tools, and create custom workflows.
3:06

Explore the dart_mcp package, a powerful framework for building Model Context Protocol (MCP) servers and clients in Dart, enabling you to connect AI models to resources, tools, and create custom workflows.

Flutter

23,167 просмотров • 3 месяцев назад

‼️WHY TODAY IS A BIG DAY FOR INTERNET COMPUTER PROTOCOL DFINITY Foundation's Internet Computer Protocol is set to unveil caffeine v3.0 today, April 7. According to the announcement made by Dom Williams (dom | icp), it will kickstart a new era on ICP. The update introduces "Cloud Engines," enabling enterprises to deploy private subnets using a mix of sovereign nodes and traditional AWS instances to achieve specialized throughput. Bullish for the ICP ecosystem.
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‼️WHY TODAY IS A BIG DAY FOR INTERNET COMPUTER PROTOCOL DFINITY Foundation's Internet Computer Protocol is set to unveil caffeine v3.0 today, April 7. According to the announcement made by Dom Williams (dom | icp), it will kickstart a new era on ICP. The update introduces "Cloud Engines," enabling enterprises to deploy private subnets using a mix of sovereign nodes and traditional AWS instances to achieve specialized throughput. Bullish for the ICP ecosystem.

BSCN

15,328 просмотров • 3 месяцев назад

🚀 Fresh in the BApp Store: MCP Server Link Burp Suite to your AI clients with the Model Context Protocol. 🧠 Integration with Claude Desktop? Easy-peasy. 🛰️ Need a Stdio MCP proxy? Locked and loaded. 🔓 Unlock new LLM workflows.
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🚀 Fresh in the BApp Store: MCP Server Link Burp Suite to your AI clients with the Model Context Protocol. 🧠 Integration with Claude Desktop? Easy-peasy. 🛰️ Need a Stdio MCP proxy? Locked and loaded. 🔓 Unlock new LLM workflows.

BApp Store

62,397 просмотров • 1 год назад

Today we open Laravel MCP (beta) to the public! Laravel MCP is a library that makes it simple to build Model Context Protocol servers in your Laravel apps. This gives AI clients (like Claude, Cursor, & ChatGPT) a structured way to interact with your application. It's already been field tested by powering Laravel Boost.
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Today we open Laravel MCP (beta) to the public! Laravel MCP is a library that makes it simple to build Model Context Protocol servers in your Laravel apps. This gives AI clients (like Claude, Cursor, & ChatGPT) a structured way to interact with your application. It's already been field tested by powering Laravel Boost.

Laravel

78,033 просмотров • 10 месяцев назад

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:
1:48

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

81,696 просмотров • 10 месяцев назад

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 просмотров • 1 год назад

🚨JUST IN: CAFFEINE V3.0 OPENS A NEW ERA ON ICP IN A FEW DAYS DFINITY Foundation's Internet Computer (ICP) is scheduled to launch the Caffeine v3.0 upgrade on April 7th, enabling natural language-based application development. According to Dominic Williams (dom | icp), the update introduces "Cloud Engines," enabling enterprises to deploy private subnets using a mix of sovereign nodes and traditional AWS instances to achieve specialized throughput. A new "Internet Intelligence Network" (IIN) is being proposed to provide verifiable AI inference at lower costs than centralized GPU clouds.
0:30

🚨JUST IN: CAFFEINE V3.0 OPENS A NEW ERA ON ICP IN A FEW DAYS DFINITY Foundation's Internet Computer (ICP) is scheduled to launch the Caffeine v3.0 upgrade on April 7th, enabling natural language-based application development. According to Dominic Williams (dom | icp), the update introduces "Cloud Engines," enabling enterprises to deploy private subnets using a mix of sovereign nodes and traditional AWS instances to achieve specialized throughput. A new "Internet Intelligence Network" (IIN) is being proposed to provide verifiable AI inference at lower costs than centralized GPU clouds.

BSCN

30,136 просмотров • 3 месяцев назад

🇸🇦🇺🇸 DAVID SACKS: MCP IS THE NEXT BIG WAVE IN AI "MCP {Model Context Protocol} is a new standard that allows agents to talk to existing SaaS applications or any kind of application, and it's really going to enable this agentic future that I think is the next big wave in AI." Source: David Sacks
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🇸🇦🇺🇸 DAVID SACKS: MCP IS THE NEXT BIG WAVE IN AI "MCP {Model Context Protocol} is a new standard that allows agents to talk to existing SaaS applications or any kind of application, and it's really going to enable this agentic future that I think is the next big wave in AI." Source: David Sacks

Mario Nawfal

123,166 просмотров • 1 год назад

1/n: 🤖 I just built a production-ready crypto Telegram bot in ONE day with Claude + MCP integration. AI coder agents are already a reality and if you're not leveraging MCP servers right now you're missing out on some serious productivity gains. Get a local AI agent in 5 minutes with Anthropic's new open-source server protocol for LLM connections. 🧶
0:22

1/n: 🤖 I just built a production-ready crypto Telegram bot in ONE day with Claude + MCP integration. AI coder agents are already a reality and if you're not leveraging MCP servers right now you're missing out on some serious productivity gains. Get a local AI agent in 5 minutes with Anthropic's new open-source server protocol for LLM connections. 🧶

kaue

10,596 просмотров • 1 год назад

Already know the basics of the Model Context Protocol? On July 18, I’m running a live, hands-on workshop covering advanced MCP features—sampling, elicitation, advanced tools, and more. If you want to build real, production-ready AI integrations, this is for you.
1:01

Already know the basics of the Model Context Protocol? On July 18, I’m running a live, hands-on workshop covering advanced MCP features—sampling, elicitation, advanced tools, and more. If you want to build real, production-ready AI integrations, this is for you.

Kent C. Dodds 🏹

48,404 просмотров • 1 год назад

🚀 Webhash now supports deployment to the DFINITY Foundation's Internet Computer (ICP). You can build a decentralised website visually, connect your DNS domain, and launch it to ICP, all in minutes, without writing a single line of code. Watch the full flow in the attached demo 🎥 🌐 Try it yourself: We are DFINITY Developers ∞ 🚀
2:18

🚀 Webhash now supports deployment to the DFINITY Foundation's Internet Computer (ICP). You can build a decentralised website visually, connect your DNS domain, and launch it to ICP, all in minutes, without writing a single line of code. Watch the full flow in the attached demo 🎥 🌐 Try it yourself: We are DFINITY Developers ∞ 🚀

webhash.eth

21,122 просмотров • 1 год назад

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇
2:24

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

Taranjeet

471,972 просмотров • 1 год назад

📣 Today, I’m excited to walk you through Unity’s NEW AI offering, Meta MCP Extensions, and agentic tools to demonstrate how we can 𝗕𝘂𝗶𝗹𝗱 𝗔 𝗙𝘂𝗹𝗹 𝗩𝗥/𝗩𝗥 𝗚𝗮𝗺𝗲 from start to finish using these AI tools in a practical way. 🎥 Full video available at: 📌 Here’s what I’m covering today: - Unity VR project setup (with OpenXR plugins) - Installing the Unity AI Assistant and demos - Configuring Unity MCP + Meta MCP Extensions - Configuring Claude Code & MCPs - Building a VR/MR Basketball Game with the Unity AI Assistant, Claude Agent, and external Claude Code CLI - A lot of iteration with Claude Code + the Meta XR Simulator 💡Also, it’s been a while since I've posted a new video, and I’m genuinely excited to be back, especially with a topic like this that I know many devs have been waiting for.
0:21

📣 Today, I’m excited to walk you through Unity’s NEW AI offering, Meta MCP Extensions, and agentic tools to demonstrate how we can 𝗕𝘂𝗶𝗹𝗱 𝗔 𝗙𝘂𝗹𝗹 𝗩𝗥/𝗩𝗥 𝗚𝗮𝗺𝗲 from start to finish using these AI tools in a practical way. 🎥 Full video available at: 📌 Here’s what I’m covering today: - Unity VR project setup (with OpenXR plugins) - Installing the Unity AI Assistant and demos - Configuring Unity MCP + Meta MCP Extensions - Configuring Claude Code & MCPs - Building a VR/MR Basketball Game with the Unity AI Assistant, Claude Agent, and external Claude Code CLI - A lot of iteration with Claude Code + the Meta XR Simulator 💡Also, it’s been a while since I've posted a new video, and I’m genuinely excited to be back, especially with a topic like this that I know many devs have been waiting for.

Dilmer

24,796 просмотров • 2 месяцев назад

This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.
4:30

This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.

Theoriq

82,463 просмотров • 1 год назад

Photoshop AI Agent / MCP example (using Claude), where I couple it with an image vision MCP to have Claude AI rename the layers in a Photoshop file based on the content of the layers. Thanks to Paul Trani for supplying a Photoshop file with a typical naming scheme (none).
0:37

Photoshop AI Agent / MCP example (using Claude), where I couple it with an image vision MCP to have Claude AI rename the layers in a Photoshop file based on the content of the layers. Thanks to Paul Trani for supplying a Photoshop file with a typical naming scheme (none).

Mike Chambers

16,689 просмотров • 1 год назад

👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡
1:33

👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡

GitHub

35,316 просмотров • 1 год назад

In this video, we break down the Model Context Protocol — a massively underrated concept in AI that's quietly redefining what large language models can do. While most people are distracted by the hype, MCP is solving a core problem: LLMs that can perform actions. We dive into: 1. The limitations of current AI systems 2. What makes MCP different 3. How MCP can reduce engineering overhead 4. Real-world scenarios where MCP shines 00:00 What is MCP? 01:48 Usecase - SEO 03:50 Usecase - RAG 04:50 Usecase - Apps 06:30 Conclusion 07:00 The future? #MCP #AI #LLM
9:17

In this video, we break down the Model Context Protocol — a massively underrated concept in AI that's quietly redefining what large language models can do. While most people are distracted by the hype, MCP is solving a core problem: LLMs that can perform actions. We dive into: 1. The limitations of current AI systems 2. What makes MCP different 3. How MCP can reduce engineering overhead 4. Real-world scenarios where MCP shines 00:00 What is MCP? 01:48 Usecase - SEO 03:50 Usecase - RAG 04:50 Usecase - Apps 06:30 Conclusion 07:00 The future? #MCP #AI #LLM

Gaurav Sen

41,117 просмотров • 1 год назад