WEBVTT

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Okay, let's dig in.

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So first up we used the Fire Crawl MCP server five times.

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And these were in fact all fire crawl searches.

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All five of them.

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I looked through them.

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And that's interesting.

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Last time I did five searches and then a bunch of scrapes.

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This time it didn't bother with the scrapes.

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It decided it had enough information from from these searches that it was good to go.

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And that's okay.

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The reason that we love Agentic AI is because we want the LLM to make its own decision about what it

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wants to do next, based on the information it has to hand, and that is what it decided.

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If we wanted it to be rigid and we wanted it to always first do a search and then do a scrape, then

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we should set up separate workflows steps and use something like structured outputs and different prompts

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to make it operate in that regimented way.

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But the idea of Agentic AI is no.

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Let the LLM decide based on the information it has to hand.

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And that is exactly what we did.

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Okay.

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So how about these 13 uses of Hunter.

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So in fact it was all using different email tools.

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So Hunter has a bunch of them.

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It was using a the email finder and the email verifier to check emails.

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And it was also using something else as well.

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I seem to remember hang on, it was using domain search as well.

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So it was using a bunch of different tools that that that Hunter makes available to try and really dig

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in to, to make the best shot at finding a reliable email address.

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So it really took the time over that, and that's pretty cool.

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And that's why as a result, we end up with this results with five good prospects here, starting with

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Yuval Adson, uh, Atzmon from McKinsey and company, uh, the senior partner and CFO at McKinsey.

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And with this, that apparently is a very good guess, a very good prediction of his email address.

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Um, from Hunter.io.

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And then this is the CFO of BCG.

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And similarly that's a very credible looking email courtesy of Hunter.io.

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And you'll find the same for the others.

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And hopefully you have something similar.

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So this is really great to see.

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If you look here by the way you can see the whole flow of everything that happened.

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An awful lot happened.

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This was a pretty sophisticated workflow.

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And let's face it, it was actually pretty easy just adding these two MCP clients.

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There really wasn't much to it.

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In fact, the hardest part of all this was just explaining all the terminology about MCP, MCP, client

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and host and server and streamable, HTTP and everything else.

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Actually using MCP was super easy and that's how it often is.

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MCP is very easy to use.

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We just bunged on extra tools here.

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Now I have a secret that I should reveal, which I didn't want to reveal it, but I probably should

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that whilst what we did with Fire Crawl was totally legit because Fire Crawl doesn't have tools.

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It turns out that, uh, that, uh, Hunter.io does, in fact have a tool.

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And so we could have just used the tool right here instead of using MCP.

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But one thing is that we would have then had to have picked these three things separately and had three

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separate tool operations, and it would have been more messy and more clunky.

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So it was easier perhaps to use MCP, but that is a bit of a stretch.

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The bottom line is, if you can use an na n node, you're probably should.

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And I had a really hard time finding things that didn't already have an N nodes.

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Uh, that.

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Which is why we've used this this, uh, Hunter MCP client.

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Anyway, just so we could put MCP to good use.

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But the fire crawler one was totally legit.

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That one I stand behind.

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But anyway, here we go.

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We've explored and we've used MCP servers.

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Uh, we've built the MCP clients to connect to the MCP servers other people have provided and they've

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worked great for our business objective.

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Okay, now we're gonna do something crazy.

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We're going to turn all of this into an MCP server so that someone else can use it.

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Which is confusing because this itself contains MCP clients which call other MCP servers.

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But we're going to package all of this up to make it into a tool which the outside world can use.

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Are you ready for this?

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That's what we're going to do now.

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I'm going to do it quite fast and I will do recaps another time.

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And it's not a common task that you'd often want to do this.

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So it's more for the show of it.

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So let's let's go and do it.

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Okay.

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First up I'm going to do something crazy.

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I'm going to delete this chat message thing here.

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I'm going to add a new trigger.

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And the trigger is going to be when executed by another workflow, meaning that this whole workflow

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is going to become something that can be called by another workflow.

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And, and I'm going to have it have one input field, which is going to be query, which is going to

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be the user's question, so that the query has to be passed in to this workflow and that will trigger

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this whole thing running.

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So far you may be only half with me, but when I escape, here we go.

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When executed by another workflow, this is the new trigger.

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This is replacing the chat window.

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And so now I just have to edit this agent.

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It can't be that anymore.

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It's not connected to a chat trigger node.

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We need to define it and we're going to define it.

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Can you think we're going to define it.

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What do you think it's going to be.

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It's going to be JSON query.

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We want to take the query fields from what comes in okay.

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So what comes in is then going to to be passed in here as the query okay I'm also going to name this.

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It's currently called my workflow 18.

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And I'm going to call it something different I'm going to have it be called prospecting.

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Prospecting I'm going to call it Subagent.

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Now, that might sound fancy to you.

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My point is that since this is itself a whole agent flow that can be kicked off by another workflow,

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then this whole thing is what we could describe as like a subagent.

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It's an agent that could run as part of some bigger, grander plan.

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And we're going to cover some agents tomorrow.

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So you don't need to worry too much about this, but just get a sense.

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We're calling this prospecting Subagent because it's able to prospect, and it is a little agent that

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can be within a bigger, grander plan.

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All right.

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Okay.

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Back to amplify again.

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Now in MCP, we have prospecting subagent.

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Let's make a new workflow.

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And this time we're going to call it prospecting MCP.

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Here we have it.

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And I'm going to add a step which is going to be an MCP server trigger.

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Expose tools as an MCP server endpoint.

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So here we go.

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I open this up and look.

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It's given me some URLs.

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It's given me a test URL and a production URL.

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And this is a URL that you could share with somebody else to say, hey, I'm running an MCP server.

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Connect to me if you want access to my tools.

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Okay.

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So, uh, here we go.

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Here it is MCP server trigger.

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It's going to expose whatever tools we put here to the outside world as an MCP server.

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And what we can put in here can be any, any, any tools that are available from, from all the different

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tools we've looked at at the past, including like the, the, the, um, not the firewall tool, the,

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the, uh, Hunter tool, it could be any tool that you found from your list of tools, but we don't

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want to expose any old tool.

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We don't want to expose Hunter.

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We want to expose the prospecting workflow that we just built as a tool for the outside world.

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So what we put in here is call and workflow tool, a tool which can call an entire workflow.

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Now that is starting to make some sense.

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And from this list we need to choose the workflow.

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The problem is we first need to publish the workflow we just made so that we can pick it from this list.

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Let's go and do that.

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Okay.

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First I press on amplify.

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I go to MCP.

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I go back to my subagent where we were just a minute ago.

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And I press publish and I say publish.

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And now a little green tick here appears to say this is published.

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Back to amplify back into MCP and to prospecting MCP.

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And here we are.

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And now we can open this guy up and we should be able to connect to our workflow.

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Let's see.

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And when I click here you should certainly see.

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I hope that there will be a prospecting subagent that appears on the list, and we just need to do a

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few more things.

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We need to describe this tool.

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So I'm going to say call this tool to find sales prospects.

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For prospects for a given sales query, this tool hunts for prospective clients and returns them and

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returns five leads okay.

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And then it says here workflow inputs.

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It knows that there's one field called query.

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And we want to say that the model can define this.

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It's a tool where the model can define what that query should be.

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It's an input and we can add a description and we can say, uh, state.

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Uh, what kind of, uh, sales prospect you are looking for such as?

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Such as find five.

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Yes.

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I don't think the five.

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Yeah.

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Fine.

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Find uh, um, uh, suitable, um, accountants.

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In the, uh, us to sell accounting software.

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Okay, that's a good example.

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I'm going to take out the number five there.

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Just have it be.

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Returns.

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Leads.

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Okay, great.

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There is our description.

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We have done that.

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I'm going to save and come back.

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And we're almost ready now to actually put this to use.

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But first I want to recap what we've done.
