Anthropic's New Agent Protocol!

Key Takeaways

okay so while people are waiting for the latest series of new models the GPD 5S the Gemini 2s the clawed floors one of the things that people really Overlook is that the real power of llms nowadays is mostly coming from what you put in the context window that you're sending to the llm and that means getting the right data at the right time for whatever particular query that you want to do of the llm as we know all the llm have a cut off date meaning that they don't have any information in them after that training cut off date but certainly over the last few months we've seen a lot of the big providers start to incorporate search into their online apps for their particular LM so for example we saw open AI have GPT search we've seen Google add Google search context grounding and the one big player that's been missing in this has been anthropic that's until now so this video I'm going to talk about what anthropic has announced with their model context protocol I'm going to talk about how it takes some of these ideas Way Beyond what other people have been looking at and how it stands a really strong chance of becoming the fundamental protocol for agents going forward so the idea of basically giving an llm some kind of protocol to be able to refer to other data is not new if you think back to chat GPT plugins back in March 2023 three this is exactly what open AI were trying to do they were basically trying to give people a way to Ping external websites maybe that was going to be Bing search maybe that was going to be a whole bunch of things it didn't take off the implementation of it was not great and you can imagine that anthropics been sitting on the sidelines thinking for quite a while how are they going to do this and the way that they've done this is not to specifically provide a search function themselves or any sort of unique thing like that what they've developed is an open sourcing protocol now this is what they're calling the model context protocol and the idea here is that this is a way to connect llms to data and to systems of data you could also think of it as tool use that you're connecting these models initially in this case it's going to be the clawed Sonet 3.5 model to external data both for coming in and for sending it back to that tool so what anthropic is proposing here is an open standard that everybody used not just for anthropic models but for other models so that people can start to build tools that you could swap in llms easily you could swap out tools for llms easily that you have a real Plug and Play kind of system going on here if we look at the model context protocol we can see that the key thing here is that this is a two-way connection between data sources and their host now they're talking about AI powered tools here really what they're talking about is the host which currently today is going to be the claw desktop app but you could imagine very quickly it's going to be a vs code integration it's going to be something that's built into some kind of slide tool and what this protocol does is it allows the llm to be able to call these external data sources and to be able to bring them in so that it can use them for particular queries that the user has now there could be simple things like asking what's the weather in a particular location right through to replacing things like code editors where suddenly you just have a plugin in vs code and the llm can basically tell that plug-in to create these files populate them with this code run some test to see if it worked and send that back to the llm so really this is going to be like a backbone behind everything that's going to be running agents here so if we jump in and look at the docs here we can see this diagram which kind of explains a lot of this so you've got this sort of NCP host and this is going to be like your VSS code like I mentioned currently it's the claw desktop app and the claw desktop app is out there for both Mac and for Windows and for Windows r64 you can install it you can then customize it to run what's called an mCP server now these servers really can just think of them as scripts which currently are going to be things that live on your device meaning on your local computer in the future though you can imagine that they're going to be microservices as tools in the cloud and this is one of the things I've experimented a lot with Google Cloud functions is building tools that your agents can just call when they need and once you've got that tools sort of set up you can have it being used by 20 different agents it doesn't matter I going to feel like this is going to take this idea to the next level with this protocol to do this so if we look at the diagram we've got the claw desktop app as being the host once it's set up and I'll show you after this how to do the actual setup and stuff like that it can then call a number of servers now you could imagine that one of these servers is going to be a search service so in their example servers that they give you a brave search for this but the thing is that they've actually already opened a bunch of these mCP servers so you can see we've got a file system one for being able to change things in our file system we've got GitHub to be able to access things in GitHub and that includes reading from GitHub and also pushing to GitHub which is you know interesting and then there are a whole bunch of things around scraping memory slack Integrations Etc and the really cool thing is not only have they given you a bunch of pre-built servers but they've published an SDK in fact two sdks both a typescript SDK and a python SDK for you to be able to create these servers yourself so I'm going to have a look at the basics in this video but certainly in future videos I think we'll look at actually just building full-on agents that you can have doing things where you've got these servers that are going back and forth to the llm host as you go along now the idea is that once you've got this server set up so let's say this is brave search we can also then populate it with another one say GitHub or a custom rag database for your particular information and look at this third example is that even though currently we need to have the servers I think running locally on our machines you can have those servers call external apis so already if you've got some kind of database in the cloud if that's a chroma DB if that's a p cone DB Etc very quickly my guess is you're going to see Integrations come out so that you'll be able to wire your local server up to things in the cloud like that and then be able to pull that data back to the host that you're using now remember at the moment the only host I think that's out there is the claw desktop app I would imagine you'll see the Integrations come for a lot of the low code no code sort of agent tools that are out there Etc so the simplified way of thinking about how this actually works is that you've now got a protocol that can give your llm a whole Suite of tool uses that you can create that you could just plug in for your usage so to get started started using this you're going to need to install the claw desktop app and that app will work whether you've got a free account or a paid account that doesn't matter I'm going to walk through doing the setup on my Mac but they have instructions in here of how you can do this for Windows as well and then we'll look at adding some NCP servers and perhaps how we could create something custom ourselves okay so the first thing that you want to do is to see where you've got the CLA application support now in the Mac this is going to be in your library application support Claude in here and what I'm going to do is just CD into that once I've done that I can then open this up with my IDE so in this case I'm going to be using cursor as the IDE but you could use vs code where you just have code dot Etc now what you're going to want to do is whether you do this in cursor or in the terminal is you want to be able to create a new CLA desktop config so if I come in here I'll just do it in the terminal here we'll see that if we go back now to our cursor we've got this config here and this is where we're going to paste in the server information and by server really we're just pointing to a script right we're not connecting to the cloud or anything with this part of it but this is so that Claude desktop will be able to actually use these for accessing things so we'll come back to this and let's look next at how to actually set up some of these servers okay so to get started with trying out some of their pre-made mCP servers you can just come over to the GitHub Linked In the docs and you'll see that they have got a whole bunch of pre-made servers that are in here let's look at for example the brave search one we can see that these are actually made in typescript if we wanted to see actually what it does what the prompt is and stuff like that this is the tool definition so this is actually telling Claude what it's going to actually use in here and what the schema of it is what it expects the search query to be what expects the number to be Etc going through this so it's got a bunch of different search things in here and you can see they've got something similar for the file system so if you want to be able to read write files to your local directories Etc this is something that you can do in here so when you come in here the definitions for these these you don't need to install basically the first time it runs it will install it in here for you but what you'll need to do is give it access to which folders Etc that it can you know that it can access in here so you want to get these definitions in this case for the file system for the brave search and actually for the brave search you're going to need to go and set up an API key for that it's quite simple just follow the directions in here you set up a free account and then you can use this and then we're going to do is copy these all across now you can see here I've got the brave search set up we set up our mCP servers which is going to be an object that contains Brave search I'm going to have file system I'm going to have Puppeteer in here for doing this now once that's done you want to launch the CLA desktop so you can see here I've basically just launched this now there is a couple of ways that you can see if your tools have been loaded so if you come over here we can see we've got 16 mCP Tools in here so you can see we've got a brave search web search local search we've got create directory these are from the file tools so I think the file tools has nine different things that you can do here we can list out directories that kind of thing and then we can see we've got the Puppeteer Tools in there as well for being able to navigate to a URL to be able to get some details out that kind of thing as we go through here all right okay so if I wanted to do a normal search I can do a search with it um let's give it something a little bit more challenging okay now first off I'm going to tell it to basically go to the Venture beat site and extract out the titles about anthropic so the idea here is that we wanted to use Puppeteer to actually do this so it's going to ask us can use Puppeteer I'm going to say yes if you look already it's opened up Google Chrome for testing and it's asking me now can it use another tool for evaluating from properer I'm going to allow that we can see that actually what what it's searching for in here is we can see that okay it's looking for a different kind of H2 H3 tags and here and sure enough it's come back it says I I found several recent articles about anthropic on Venture beat here are the titles and then anthropic releases model context protocol anthropic bets on personalization so let's come over and have a look okay so sure enough if we come over to venture be we can see the anthropic releases model context we can see anthropic bets on personalization and I think it had one more about yes Amazon doubles down on anthropic so we can see that it's gotten all of those and it's got another one as well in there okay now if we want to save that and use a different tool I can just put in save those into a text file in agents CLA saves so I've made a a folder specifically where it can do this and you can see sure enough it's going to ask for create directory so it's going to check that the directory is there and do a whole sort of if exists kind of thing and then it wants to be able to list from the directories and then be able to write to the file system so at the moment you need to approve everything that it does each time and this can be a little bit frustrating my guess is at some point you'll be able to just approve certain ones so that they work in all of your chats but I guess it makes sense that you know is able to do this okay so looking at this it's basically saying that it saved it as Venture beat and Thro articles if I just bring over that folder sure enough we can see that folder is there and if we come down and look at it we can see that the the titles have been extracted out nicely so just using this we'll be able to do this kind of thing now with properer you can also do things like capture a screenshot of a website you can do a whole bunch of different things in here so this was using their pre-made servers that we looked at now as I mentioned earlier on they have two sdks that you can make your own mCP servers so they have a python SDK and they have a typescript SDK what I'm going to do is leave it here for this video and in the next video I'll walk through step by step actually making some of our own tools and showing you how to use the SDK how to point the mCP server where your tool code is actually going to be and some tips and tricks of things you want to be warry about when you're going to be cramming a lot of tools into this kind of thing so anyway just to finish up I would say that this is definitely a big deal and the reason why is that they've made the whole protocol open source they've allowed people to use it not just for their models for any models my guess is pretty quickly we will see other people adopt this and it will become more of a standard now it will be interesting to see how does open AI react to this do they get on board or do they insist on having their own standard for this kind of thing you could imagine this combined with things like artifacts inside of the cord desktop app you can now do a whole lot more with those artifacts that you couldn't do before and in some ways you're going to be able to design your own sort of cursor editor bolt edit different sort of AI coding editors and I think we're going to see this for a lot of different ideas going forward anyway I'd love to hear from you in the comments about what tools you would most like to see implemented with this I will put something together for the next video as always if you found the video useful and you want to be reminded about the next one please click on subscribe and I will talk to you in the next video bye for now