Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Internet Identity is getting an MCP server. We sat down with Arshavir Ter-Gabrielyan to understand what it is and why it matters. He starts with the problem: an AI agent runs in a cloud sandbox. No access to your device. No safe way to hold your keys. The MCP... show more

DFINITY Foundation

694,013 subscribers

26,677 views • 2 days ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Your AI agent has your API keys. A poisoned document tells it to curl your secrets to an attacker's server. This is credential exfiltration, and it's the #1 risk in agentic AI right now. The fix is removing the secret from the agent entirely. Agent Vault sits between your agent and the APIs it calls. The agent gets dummy credentials, and Agent Vault swaps in the real ones at the network layer. The agent never sees your keys. We just dropped a full video + guide on connecting Hermes Agent to Agent Vault on a VPS!

Your AI agent has your API keys. A poisoned document tells it to curl your secrets to an attacker's server. This is credential exfiltration, and it's the #1 risk in agentic AI right now. The fix is removing the secret from the agent entirely. Agent Vault sits between your agent and the APIs it calls. The agent gets dummy credentials, and Agent Vault swaps in the real ones at the network layer. The agent never sees your keys. We just dropped a full video + guide on connecting Hermes Agent to Agent Vault on a VPS!

Infisical

85,904 views • 2 months ago

Build your first AI agent + MCP Server in Python. Here is everything you need to build your first AI agent in less than 20 minutes. About the code you'll see here: 1. I used Google ADK with Gemini Flash to power the agent 2. The agent connects to an MCP server 3. It also uses two custom tools to do its work 4. You can see everything the agent does thanks to Comet's Opik library Here is the video, free for you to watch.

Build your first AI agent + MCP Server in Python. Here is everything you need to build your first AI agent in less than 20 minutes. About the code you'll see here: 1. I used Google ADK with Gemini Flash to power the agent 2. The agent connects to an MCP server 3. It also uses two custom tools to do its work 4. You can see everything the agent does thanks to Comet's Opik library Here is the video, free for you to watch.

Santiago

56,569 views • 1 year ago

SEV Subnets are now live on the Internet Computer. We sat down with Björn Tackmann to understand what they actually are and why they matter. He starts with the problem: standard cloud infrastructure writes your data to memory in plaintext. Anyone with access to the hardware can read it. That's not a flaw in any specific product. It's how computers work. SEV Subnets are the Internet Computer's answer to that. Full conversation below.

SEV Subnets are now live on the Internet Computer. We sat down with Björn Tackmann to understand what they actually are and why they matter. He starts with the problem: standard cloud infrastructure writes your data to memory in plaintext. Anyone with access to the hardware can read it. That's not a flaw in any specific product. It's how computers work. SEV Subnets are the Internet Computer's answer to that. Full conversation below.

DFINITY Foundation

36,270 views • 23 days ago

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Santiago

51,527 views • 1 year ago

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!

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 views • 1 year ago

KYC verifies the human. But your agent? It has no identity. No name. No way to prove who it's acting for. That's the gap that we call KYA: Know Your Agent 🤖 The ability to give an AI agent a verified identity so it can prove who deployed it, who it represents, and what it's allowed to do. Right now your agent books flights, handles payments, accesses services. Flying blind on your behalf. That's not trust. That's assumption. KYA is the infrastructure that changes this. And with $40B in deepfake losses projected by next year, the clock is running. Our CEO & Cofounder Evin evin sat down with amanda.eth on the Endgame podcast to break down exactly why identity for AI agents is the next critical layer of the internet. Full episode 👉

KYC verifies the human. But your agent? It has no identity. No name. No way to prove who it's acting for. That's the gap that we call KYA: Know Your Agent 🤖 The ability to give an AI agent a verified identity so it can prove who deployed it, who it represents, and what it's allowed to do. Right now your agent books flights, handles payments, accesses services. Flying blind on your behalf. That's not trust. That's assumption. KYA is the infrastructure that changes this. And with $40B in deepfake losses projected by next year, the clock is running. Our CEO & Cofounder Evin evin sat down with amanda.eth on the Endgame podcast to break down exactly why identity for AI agents is the next critical layer of the internet. Full episode 👉

Billions

31,142 views • 4 months ago

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.

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 views • 1 year ago

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:

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 views • 10 months ago

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

Tyler Shukert

203,451 views • 1 year ago

🖼️ Introducing Open Multi-Agent Canvas - with MCP Chat with multiple LangGraph agents and any MCP server inside of a canvas app. Powered by CopilotKit🪁, LangChain & Larinháh Here's an example of how we used it to plan our offsite. We connected an agent to the Google Maps API, had it find local spots, and then sent the itinerary directly to Slack via MCP to be reviewed by the team. Explore and extend:

🖼️ Introducing Open Multi-Agent Canvas - with MCP Chat with multiple LangGraph agents and any MCP server inside of a canvas app. Powered by CopilotKit🪁, LangChain & Larinháh Here's an example of how we used it to plan our offsite. We connected an agent to the Google Maps API, had it find local spots, and then sent the itinerary directly to Slack via MCP to be reviewed by the team. Explore and extend:

CopilotKit🪁

22,080 views • 1 year ago

MCP sucking is a harness problem, not an MCP problem MCP unlocks behavior that is fundamentally impossible to get via CLI or APIs Bad auth, too much context usage, all get solved with an execution layer - your agent writes code to progressively discover and call tools

MCP sucking is a harness problem, not an MCP problem MCP unlocks behavior that is fundamentally impossible to get via CLI or APIs Bad auth, too much context usage, all get solved with an execution layer - your agent writes code to progressively discover and call tools

Rhys

376,613 views • 4 months ago

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

Santiago

39,944 views • 1 year ago

happy friday. sneak peek at some new features i'm building for the bankr agent: > sandboxed filesystem (your agent gets its own secure file system in the browser. you control what it can access. no agent running loose on your actual computer) > skill uploads (plugin new capabilities so your agent learns new things) > cli download & access > secure environment variables for api keys > github integration (connect your repo for reads and writes directly from your agent) all of this runs in a secure browser environment. no desktop app. no messy configuration. no downloading agent harnesses from the terminal. just a sandbox you control. in the video: i download an audit skill, run it against a smart contract, and save the report straight to the filesystem. then i ask the agent to pull all my 2026 transactions and write a csv for my accountant.

happy friday. sneak peek at some new features i'm building for the bankr agent: > sandboxed filesystem (your agent gets its own secure file system in the browser. you control what it can access. no agent running loose on your actual computer) > skill uploads (plugin new capabilities so your agent learns new things) > cli download & access > secure environment variables for api keys > github integration (connect your repo for reads and writes directly from your agent) all of this runs in a secure browser environment. no desktop app. no messy configuration. no downloading agent harnesses from the terminal. just a sandbox you control. in the video: i download an audit skill, run it against a smart contract, and save the report straight to the filesystem. then i ask the agent to pull all my 2026 transactions and write a csv for my accountant.

deployer

45,638 views • 3 months ago

⚡day 5 of launch week: from (zero) MCP server to ChatGPT app this is peak developer experience 🤌🏼 1. define your UI in a single react file. 2. test it instantly with hot reload in the built-in Inspector 3. deploy it in one click on mcp-use Cloud 4. ship it directly to ChatGPT with: npx create-mcp-use-app@latest my-server --template apps-sdk you can go from zero to a deployed mcp server with apps sdk widgets in just 5 minutes here's how 🧵

⚡day 5 of launch week: from (zero) MCP server to ChatGPT app this is peak developer experience 🤌🏼 1. define your UI in a single react file. 2. test it instantly with hot reload in the built-in Inspector 3. deploy it in one click on mcp-use Cloud 4. ship it directly to ChatGPT with: npx create-mcp-use-app@latest my-server --template apps-sdk you can go from zero to a deployed mcp server with apps sdk widgets in just 5 minutes here's how 🧵

pederzh

22,647 views • 8 months ago

Agent-in-the-browser unlocks superpowers. The magic really shines when you bring your own model, system prompts, and MCP tools into the mix. Hence, AgentBoard 🪄. Your models, keys, and settings. Integration with remote MCP servers and — this is where it gets really fun — ability to register and allow the agent to call custom ~WebMCP tools that execute in context of the page. Chrome Web Store: Code:

Agent-in-the-browser unlocks superpowers. The magic really shines when you bring your own model, system prompts, and MCP tools into the mix. Hence, AgentBoard 🪄. Your models, keys, and settings. Integration with remote MCP servers and — this is where it gets really fun — ability to register and allow the agent to call custom ~WebMCP tools that execute in context of the page. Chrome Web Store: Code:

Ilya Grigorik

22,961 views • 9 months ago

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!

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 views • 10 months ago

Doom is now an MCP App 🎮 Waiting for the build in Visual Studio Code just got fun with your favorite arcade games! Runs on all MCP Apps hosts: Claude, goose, Postman, and more. My server pulls the games from the awesome Internet Archive. Check it out!

Doom is now an MCP App 🎮 Waiting for the build in Visual Studio Code just got fun with your favorite arcade games! Runs on all MCP Apps hosts: Claude, goose, Postman, and more. My server pulls the games from the awesome Internet Archive. Check it out!

Ido Salomon

15,003 views • 5 months ago

I'm still picking my jaw off the floor with this MCP update: Postman will now automatically build an MCP server for an API. Automatically! You select your API and the requests you want to include, and Potman will generate a Zip file with everything you need. In collaboration with Postman, I recorded a video showing how I generated an MCP server for the Google Maps API. It's glorious! Also, and before I forget: You can now test any MCP server with your Postman application. They built MCP right in, so now you can: • Connect to an MCP server • List out all of the available tools • Test any of the tools This is a 10x boost for the MCP ecosystem. If you've tried the default MCP debugger, you'll understand how huge a deal it is that you can do all of that from Postman now. Go here to give this a try:

I'm still picking my jaw off the floor with this MCP update: Postman will now automatically build an MCP server for an API. Automatically! You select your API and the requests you want to include, and Potman will generate a Zip file with everything you need. In collaboration with Postman, I recorded a video showing how I generated an MCP server for the Google Maps API. It's glorious! Also, and before I forget: You can now test any MCP server with your Postman application. They built MCP right in, so now you can: • Connect to an MCP server • List out all of the available tools • Test any of the tools This is a 10x boost for the MCP ecosystem. If you've tried the default MCP debugger, you'll understand how huge a deal it is that you can do all of that from Postman now. Go here to give this a try:

Santiago

215,727 views • 1 year ago

Supabase now has an official MCP Server! This means you can create, edit, and connect a Supabase project to your app from your AI IDE like Cursor or Windsurf! We will also be adding more features to the MCP server, such as Edge Functions and Storage, in the near future!

Supabase now has an official MCP Server! This means you can create, edit, and connect a Supabase project to your app from your AI IDE like Cursor or Windsurf! We will also be adding more features to the MCP server, such as Edge Functions and Storage, in the near future!

Tyler Shukert

85,127 views • 1 year ago