So in case there's any confusion, the most important thing that we've done today is explored how easy
it is, how incredibly easy it is to set up an AI agent, which uses a couple of different sets of tools
offered by third parties.
We do it by putting in an MCP client.
Here the MCP client connects to an MCP server.
We just give it a URL and it's able to query that server, find out what tools it offers, find out
why and then use them.
And this worked and it worked great.
And it came back with a list of real sales prospects with emails predicted.
And that was terrific.
And this is the place where you might well use MCP yourself to take advantage of all of the tools that
are out there, although of course, a bunch of them are already implemented in Nan right off the bat.
But should you find one that isn't and that you do want to use, this is ideal.
Okay.
And now we've taken it another step further, which is less common, but I want to show it to you anyway.
And it's to say, how can we build our own MCP server?
And in fact, let's put all this functionality behind an MCP server so all of this could be used.
And we've done that by, first of all, turning all this into one workflow that can be called by another.
And I called it prospecting Subagent.
And then we went to, to uh, to this to uh, here and we created a prospecting MCP, a separate workflow.
And it just contains one trigger MCP server trigger.
The outside world would hit this.
And this is where we have here our single tool.
And the tool works by calling another workflow.
And we've described what this tool does.
It finds sales prospects for a given sales query.
Okay I hope you're following this.
And if you're not it doesn't really matter.
This is a more advanced thing.
Um, but people are always interested in how you could build an MCP server.
The final thing we're going to do is actually use it.
And how do we use it?
Well, to use it we would want to have a URL.
And I'm going to go ahead.
We're going to be bold here.
We're going to we're going to push it straight to production.
And I'm going to copy this production URL.
So let me go right here.
Publish this guy.
Uh actually maybe I should save it first.
It says it's saved.
Publish it.
Publish.
And now that green check there means that it's been published.
This is out there.
It only remains now for us to actually use it.
So you might have been thinking, okay, it's cool that we've made an MCP server that can go and do
sales prospecting, but how would we actually use this anywhere?
Like what is there available to us that can take advantage of MCP servers?
Well, actually, there's tons of things.
All sorts of applications, AI applications support MCP servers.
And one of the first and best is, of course, Claude, uh, from anthropic, the makers, the people
that invented the MCP protocol.
So here I am in Claude, and I can.
I can of course, say hi there or whatever, but I'm going to press the plus button here and I'm going
to go to add connectors down there.
And here up comes, uh, the ability to, to add a different connector to Claude.
And you can see choose from anthropic review tools, add a custom one or learn more.
So I'm going to click on add a custom one, add a custom connector.
So I'm going to call it Sales Prospecting Tool.
And you can see that it hasn't used the word MCP anywhere in this terminology.
But here you can see remote MCP server URL is what it wants now.
And up to this point you might have never known what that even meant.
But now you know that I can paste in there the MCP server URL that is copied straight out of Nan, the
production one, not the test one, and this is the one that we're going to send add.
And that has just been added sales Prospecting tool.
It's in there and now we can try and use it.
Okay, let me go to a new chat.
Please use your sales prospecting tool to find, uh, people to find, uh, good targets for me to sell
my accounting software to consulting firms in the US.
Let's give this a shot.
So I am just going to call this to to to Claude just through the user interface.
So I'll use the sales prospecting tool.
So it's making a request.
Uh, it's saying can it use this sales prospecting tool.
I'm going to say I'm going to say always allow.
And did you see it had the query there.
It used the query parameter by using our MCP server and connecting to N810, it discovered that that
is the information that we want that is now calling our prospect Subagent, that is now running out
there.
Uh, and uh, momentarily, uh, when it's completed, all the various tool calls, I am very hopeful
that I will get an answer.
And I did indeed get an answer.
Here's the answer.
There are five strong prospects at US consulting firms for your accounting software, and here they
are with their email address.
And there are the five people different different set of five than before.
And uh, a great set of results.
And you can see that it called the prospecting Subagent.
And it's synthesized the, the results within Claude right here.
How about that.
We just used an AI application, Claude, and it used an MCP server that we had written and published
in Nan, and that was running in.
And that then ran a workflow which, somewhat confusingly, itself then used a couple of MCP tools too.
So we're using MCP in both directions for this.
I hope you followed it all, but if not, don't worry, we'll do a quick recap tomorrow.
And you can.
You can focus mostly on the using the tools, but I thought this was a really cool end to end example.
And just to really bring it to life back here in N810, I'm looking again at our prospecting MCP here.
If I go to executions, I'm hoping to see there we go that it was run.
It was run a few moments ago.
Uh, and if we look at the logs, we will see that the call came in fine consulting firms in the US
to sell accounting software to target midsize management consulting business advisory firms.
So a great query.
And that's why we didn't get the same set.
We got something that was more midsize companies thanks to Claude adding on that bit of context there.
So that's really great.
And this was what came back.
And these are the same, of course, as what got presented back in the Claude AI.
So so this was the result of running our MCP, our prospecting MCP workflow.
It was triggered automatically in production by Claude calling us via our MCP server.
Okay.
And if I come back here to the prospecting subagent and I look at the executions here, we will hopefully
see this one right here that also just ran.
And you will see that that was the query that was passed in.
Sure enough, this was the same, the outputs that came back and this was the bunch of MCP calls that
were made a number.
Uh it's interesting.
Let's have a look at this.
Uh, let's see what it did there.
So this time it only used Hunter because Hunter has a discover tool that is a sales prospecting tool.
Uh, and I don't believe that this tool is available, at least as of now on the the nodes.
It's only available through the MCP server.
So, so this is really cool.
We actually use functionality from Hunter that's only available, I believe, through the MCP server.
To do a specific discovery.
And so we use multiple different tools and a domain search tool and more domain searching.
And then presumably here we've got email verifier.
Uh and to to to check that the emails were accurate before it responded with the structured outputs.
So a really interesting workflow.
Maybe you have the same kind of workflow.
Maybe you have something different.
But for sure we can see that everything worked and we achieved our business outcome.
Okay.
And with that I know that we covered a lot of ground today.
I know that I went pretty fast as well.
Let me just make this nice and big again.
I want to present to you one more time our workflow.
At the end of the day, it's actually pretty simple.
We built a prospecting subagent that was able to be executed by another workflow.
It has two MCP clients, one that is Fire crawl, one that is Hunter, and it outputs in structured
output.
And it worked great.
And we also used all of this and published it as an MCP server, which we then called from Claude.
And everything worked.
And I hope it worked for you too.
Okay, so with that, we'll head over to the wrap up.
And I promised you a big day today, and I hope you agree it was a big day.
We got tons done and it was pretty satisfying.
All right, see you for the wrap.
A massive day, definitely our most advanced day so far.
We covered tons of material.
Tomorrow is a day I'm really looking forward to when we cover the great topic of context, engineering
and recap on Subagents.
And it takes just one second to pause and recognize your 87% of the way through.
Today probably felt like like it was it was a big step.
Uh, but, uh, wow, we're nearly at the finish line and oh, do I have two great days in store for
you?
I can't wait to show you.