WEBVTT

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So in case there's any confusion, the most important thing that we've done today is explored how easy

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it is, how incredibly easy it is to set up an AI agent, which uses a couple of different sets of tools

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offered by third parties.

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We do it by putting in an MCP client.

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Here the MCP client connects to an MCP server.

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We just give it a URL and it's able to query that server, find out what tools it offers, find out

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why and then use them.

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And this worked and it worked great.

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And it came back with a list of real sales prospects with emails predicted.

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And that was terrific.

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And this is the place where you might well use MCP yourself to take advantage of all of the tools that

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are out there, although of course, a bunch of them are already implemented in Nan right off the bat.

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But should you find one that isn't and that you do want to use, this is ideal.

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Okay.

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And now we've taken it another step further, which is less common, but I want to show it to you anyway.

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And it's to say, how can we build our own MCP server?

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And in fact, let's put all this functionality behind an MCP server so all of this could be used.

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And we've done that by, first of all, turning all this into one workflow that can be called by another.

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And I called it prospecting Subagent.

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And then we went to, to uh, to this to uh, here and we created a prospecting MCP, a separate workflow.

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And it just contains one trigger MCP server trigger.

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The outside world would hit this.

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And this is where we have here our single tool.

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And the tool works by calling another workflow.

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And we've described what this tool does.

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It finds sales prospects for a given sales query.

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Okay I hope you're following this.

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And if you're not it doesn't really matter.

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This is a more advanced thing.

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Um, but people are always interested in how you could build an MCP server.

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The final thing we're going to do is actually use it.

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And how do we use it?

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Well, to use it we would want to have a URL.

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And I'm going to go ahead.

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We're going to be bold here.

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We're going to we're going to push it straight to production.

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And I'm going to copy this production URL.

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So let me go right here.

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Publish this guy.

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Uh actually maybe I should save it first.

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It says it's saved.

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Publish it.

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Publish.

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And now that green check there means that it's been published.

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This is out there.

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It only remains now for us to actually use it.

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So you might have been thinking, okay, it's cool that we've made an MCP server that can go and do

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sales prospecting, but how would we actually use this anywhere?

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Like what is there available to us that can take advantage of MCP servers?

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Well, actually, there's tons of things.

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All sorts of applications, AI applications support MCP servers.

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And one of the first and best is, of course, Claude, uh, from anthropic, the makers, the people

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that invented the MCP protocol.

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So here I am in Claude, and I can.

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I can of course, say hi there or whatever, but I'm going to press the plus button here and I'm going

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to go to add connectors down there.

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And here up comes, uh, the ability to, to add a different connector to Claude.

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And you can see choose from anthropic review tools, add a custom one or learn more.

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So I'm going to click on add a custom one, add a custom connector.

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So I'm going to call it Sales Prospecting Tool.

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And you can see that it hasn't used the word MCP anywhere in this terminology.

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But here you can see remote MCP server URL is what it wants now.

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And up to this point you might have never known what that even meant.

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But now you know that I can paste in there the MCP server URL that is copied straight out of Nan, the

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production one, not the test one, and this is the one that we're going to send add.

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And that has just been added sales Prospecting tool.

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It's in there and now we can try and use it.

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Okay, let me go to a new chat.

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Please use your sales prospecting tool to find, uh, people to find, uh, good targets for me to sell

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my accounting software to consulting firms in the US.

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Let's give this a shot.

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So I am just going to call this to to to Claude just through the user interface.

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So I'll use the sales prospecting tool.

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So it's making a request.

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Uh, it's saying can it use this sales prospecting tool.

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I'm going to say I'm going to say always allow.

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And did you see it had the query there.

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It used the query parameter by using our MCP server and connecting to N810, it discovered that that

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is the information that we want that is now calling our prospect Subagent, that is now running out

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there.

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Uh, and uh, momentarily, uh, when it's completed, all the various tool calls, I am very hopeful

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that I will get an answer.

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And I did indeed get an answer.

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Here's the answer.

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There are five strong prospects at US consulting firms for your accounting software, and here they

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are with their email address.

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And there are the five people different different set of five than before.

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And uh, a great set of results.

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And you can see that it called the prospecting Subagent.

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And it's synthesized the, the results within Claude right here.

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How about that.

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We just used an AI application, Claude, and it used an MCP server that we had written and published

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in Nan, and that was running in.

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And that then ran a workflow which, somewhat confusingly, itself then used a couple of MCP tools too.

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So we're using MCP in both directions for this.

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I hope you followed it all, but if not, don't worry, we'll do a quick recap tomorrow.

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And you can.

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You can focus mostly on the using the tools, but I thought this was a really cool end to end example.

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And just to really bring it to life back here in N810, I'm looking again at our prospecting MCP here.

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If I go to executions, I'm hoping to see there we go that it was run.

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It was run a few moments ago.

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Uh, and if we look at the logs, we will see that the call came in fine consulting firms in the US

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to sell accounting software to target midsize management consulting business advisory firms.

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So a great query.

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And that's why we didn't get the same set.

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We got something that was more midsize companies thanks to Claude adding on that bit of context there.

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So that's really great.

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And this was what came back.

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And these are the same, of course, as what got presented back in the Claude AI.

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So so this was the result of running our MCP, our prospecting MCP workflow.

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It was triggered automatically in production by Claude calling us via our MCP server.

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Okay.

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And if I come back here to the prospecting subagent and I look at the executions here, we will hopefully

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see this one right here that also just ran.

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And you will see that that was the query that was passed in.

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Sure enough, this was the same, the outputs that came back and this was the bunch of MCP calls that

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were made a number.

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Uh it's interesting.

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Let's have a look at this.

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Uh, let's see what it did there.

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So this time it only used Hunter because Hunter has a discover tool that is a sales prospecting tool.

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Uh, and I don't believe that this tool is available, at least as of now on the the nodes.

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It's only available through the MCP server.

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So, so this is really cool.

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We actually use functionality from Hunter that's only available, I believe, through the MCP server.

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To do a specific discovery.

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And so we use multiple different tools and a domain search tool and more domain searching.

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And then presumably here we've got email verifier.

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Uh and to to to check that the emails were accurate before it responded with the structured outputs.

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So a really interesting workflow.

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Maybe you have the same kind of workflow.

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Maybe you have something different.

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But for sure we can see that everything worked and we achieved our business outcome.

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Okay.

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And with that I know that we covered a lot of ground today.

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I know that I went pretty fast as well.

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Let me just make this nice and big again.

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I want to present to you one more time our workflow.

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At the end of the day, it's actually pretty simple.

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We built a prospecting subagent that was able to be executed by another workflow.

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It has two MCP clients, one that is Fire crawl, one that is Hunter, and it outputs in structured

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output.

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And it worked great.

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And we also used all of this and published it as an MCP server, which we then called from Claude.

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And everything worked.

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And I hope it worked for you too.

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Okay, so with that, we'll head over to the wrap up.

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And I promised you a big day today, and I hope you agree it was a big day.

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We got tons done and it was pretty satisfying.

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All right, see you for the wrap.

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A massive day, definitely our most advanced day so far.

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We covered tons of material.

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Tomorrow is a day I'm really looking forward to when we cover the great topic of context, engineering

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and recap on Subagents.

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And it takes just one second to pause and recognize your 87% of the way through.

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Today probably felt like like it was it was a big step.

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Uh, but, uh, wow, we're nearly at the finish line and oh, do I have two great days in store for

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you?

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I can't wait to show you.
