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We have some massive news breaking out of Anthropic and that's the fact that they have just released something that they are essentially saying will change the way that AI models connect with our data. And they've released this in open source format, meaning that anyone can essentially use this new protocol. So this is a new way to connect data to AI chatbots and it's making, you know, all of the news. There's a lot of interesting things and I want to break down exactly what it's doing and some challenges I think that it may face. And it's called MCP or Model Context Protocol. So this is fascinating topic and I think this is going to have some really big implications for everything happening in AI. 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He had a thread over on X where he broke down exactly what this is and how it works and explained it very well. And some of the nuanced things that I think weren't as clear in other announcements or news articles. I like the TechCrunch one that you'll see. So they shared a quick demo of this that I also thought was really interesting. They use the Claude desktop app, right? So that's the app that can essentially run on your computer and they configured this new mpc. So essentially what this allows it to do is it's a new protocol for the AI models to connect to your data, right? So your company's documents, but also not just like, not just like data that you might want this, the models to be able to access, but also your company's internal tools. So things like Slack or Workday or, you know, anything that your company is internally using and it's got a lot of data that you want to query against, it's able to access all of it and you don't need APIs for every single tool and you know, integrate all the data in every, like, it just gets very, very complicated. So they're building one thing, they can access all of it via AI model and they want other AI model agents and companies building AI agents to use this. They've open sourced it, it's free for everyone. Now what's the likelihood of OpenAI using this? I think probably slim and I'll break that down in a minute. But first I wanted to show you a little bit of their demo. So they created a demo which essentially connected GitHub and they went and they said, hey, like, create a new repo, make a PR through a simple MCP integration. So once this new MCP was set into the Claude desktop app, the integration that they actually built took less than an hour. So really impressive, the speed and the timeline on what's actually being able to get built here. The prompt that they gave this tool in order to run this was they said make a simple HTML page, create a repository called Simple Page. Push the HTML page to the Simple Page repo, right? So the referencing GitHub, add a little CSS to the HTML page and then push it up. Make an issue suggesting that we add more context on the HTML page. Now make a branch called Feature and make that fix the push fix and push the change. Make a pull request against the main with these changes. Okay? That was the prompt that they gave it, all of that in one Prompt which you can imagine, like you still have to think this thing doesn't just magically do everything. You give it kind of an outline of what to do. And so you're kind of still thinking through the steps. And a software developer obviously thought of that and put that together, but once that's been put together, it's able to actually go and execute this. And there's kind of this little pop up that keeps coming up throughout their demo where it's like allow this tool from GitHub local and then it says run, create or Update file from GitHub and it has a warning, it says malicious MCP servers or conversation content could potentially trick Claude into attempting harmful actions through your installed tools. Review each action carefully before approving. And you have this little button where you can say allow for this chat or allow once or deny. So I think it's really interesting and they're going to run into the issue where, you know, some people are going to try to abuse this system where they're going to say they're going to tell you to, to run one of these tools that can essentially access everything on your computer and it's going to try to, you know, have some sort of malicious, it could have some sort of malicious impact on your code or other things. So either you want to be the one designing and writing that prompt or you want to carefully review it, or you want to carefully review everything that it's doing to catch some of that stuff. So anyways, but it's impressive to me that they're already thinking about that. They're already having kind of these popups, these windows, these checks in place for all of this. So a really, really impressive tool that is going to save a ton of time because it is one of the biggest pains right when you have these AI tools getting them to be able to access everything that you have, everything on your computer or within your organization. So Alex, Amber, Albert, talking about all of this, said getting LLMs to interact with external systems isn't usually that easy. Today every developer, you know, he said every developer needs to write custom code to connect their LLM apps with data sources. It's messy, repetitive work. And so essentially they're saying that they're fixing this. He said at its core, MPC follows a client server architecture where multiple services connect to any compatible client. So clients are applications like Claude, desktop IDEs or AI tools. So any really, they're building this for anyone that has an AI tool to make it easier to access data, connect to all of this stuff and Then they essentially say, you know, servers are light adapters that expose data sources. So really, really fascinating. He said part of what makes it so powerful is that it can handle both local resources, AKA your database, your files and your services, like everything on your computer and remote ones. So things like Slack and GitHub, right? These are not on your computer. These are, you know, remote things. But it's, it's handling all of them through the same protocol, which makes it much, much simpler. So with all of this, the servers are essentially sharing more than just data. They can also share files, documents, data, and they can, they can expose tools. So API integrations and prompts, right? So your templated interactions, how you actually want these tools to interact. One thing that I think is really important, a lot of people are going to be happy about is that security is built into the protocol. Servers essentially control their own resources, so there's no need to share an API key with the LLM provider. Which is interesting, right, because you can imagine if you share an API key and some sort of security breach happens or that gets leaked or something happens. API keys are very dangerous when they're out in the wild because if they're attached to some sort of platform that has a payment, someone could take your API key and rack up a massive bill on it, right? So this is something that you'd like to avoid. So it has clear system boundaries. So security is important. That's a big part of it. He said right now that this is only supported locally, so it can only run on your own computer pretty much. But they're building some remote server support and they're building enterprise grade authentication so that teams can securely share their contact sources across their organization. I think this is absolutely fascinating. And again, that demo they did was super quick, so it's really amazing that you're going to be able to access all of this. AI models really struggle when it comes to accessing all of your data and everything. And there's just a bunch of services and things that you have to build. So this is kind of one stop, one model context protocol that can access your APIs, it can access all your company's data all in one spot. Um, and if you build it, you know, with their open source tool, it's not just anthropic that can leverage it, but it's any other AI model. So they're really doing a service to the whole AI industry. Now, all of that being said, is this going to be, you know, what everyone's using? I don't think OpenAI is going to want to play ball with this. And this is because open AI, they recently essentially got a data connection feature to Chat GPT that they're, they're kind of rolling out. And the problem with it, it lets ChatGPT read code in the dev focused coding apps. So really this is focused for developers, which is kind of the same thing that the MCP is showing, also the same use cases. But anyways, what they said is OpenAI said that they're going to bring the capabilities called work with apps to a bunch of other apps in the future. But right now they're pretty much just going for trying to implement this with some of their partners. Right. So this is very different than anthropic kind of open source approach where they're letting everyone use their technology. So I think Anthrop is, is, to be honest, is going to get some kudos, is going to get a lot of traction just because it's open source and anyone can use it. So even if you're not, you know, anyone will help build that project. OpenAI and some of the other big players though, I think are going to steer clear of it because they're going to be like, no, you know, we could do it ourselves, we don't need you. I also think that right now it's going to be interesting to see, you know, how beneficial this is. If it's as good as Anthropic claims, we got to really look at it and kind of dig into it. Anthropic said. So as an example that MCP can enable an AI bot to quote, better retrieve relevant information to further understand the context around a coding task. But they didn't actually show any benchmarks to back that up. So really hoping that this is something that's powerful and positive. It looks like a really great initiative that I think is going to make it much easier. When you personally are using AI tools on your computer, it's likely you know the software you're using, if you're not a developer, the software you're using is going to be interacting with this. If Anthropic can, can get it up to snuff and can make it powerful enough and this enables them essentially to make their tools more powerful, roll out quicker. So yeah, I think that's very, very exciting and it helps them expand to a whole host of other software and tools that otherwise, you know, they have to either build their own integrations or try to use something like Zapier to connect stuff or there's a lot of complexity that they're avoiding here. So I think this is absolutely fascinating. Thank you so much for tuning into the podcast today. If you enjoyed it, if you learned anything new, if this was interesting to you, I would really appreciate a review. And again, if you are interested or you ever plan on starting a podcast, seriously, this is the week where I have a discount. I do not do this discount very often, if ever. So Black Friday use the coupon code for my podcast course. I think you will love it and it will absolutely help you launch a podcast that's completely successful. So thanks so much for tuning into the podcast today and hope you have an amazing rest of your day.