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Besides us making our own tools, it is

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also possible to consume MCP tools.

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MCP, or Model Context Protocol, you might have

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heard of.

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If you haven't, it's a protocol where others

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can expose their code, their actions, their information,

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and you to consume, so you don't need

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to use their APIs.

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A good example is GitHub, where if you

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use your GitHub MCP, it can list issues,

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create branches, and stuff like that.

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In our case, we are going to use

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the Microsoft Learn MCP server.

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So they show that they have an MCP

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server.

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There are two types of MCP servers.

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There are remote MCP servers and local MCP

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servers.

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In our case, we are going to show

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a remote MCP server because I think they

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are the future, and local MCPs are for

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niche areas in general.

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Beyond that, I'm not going to go into

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what MCP is in general unless you report

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back that you want a dedicated video on

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it.

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But just see it as someone who has

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written some code that you would not have

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had access to.

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So what we can see here is I

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have put in one more NuGet package, and

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that NuGet package is the modelcontextprotocol.

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Once we have that, we can do something

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like this.

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Await MCP client.create a new client.

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We want an HTTP client with the options

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of the endpoint being the Microsoft Learn MCP

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and its streamable HTTP.

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So here we can choose between some older

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models, and up here we can choose between

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HTTP and STDIO, which is the local.

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MCP clients come back, and you need to

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expose them, so I'm doing an await using

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here.

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But what we can do is we set

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a breakpoint here.

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We can see that whenever we have an

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MCP server, we can get what tools it

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has.

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So just like we've written some tools, Microsoft

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Learn have written some tools and exposed it

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to this URL.

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That's all there is to MCP, to be

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honest.

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So if we run it here and get

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the tools, we can see they have three

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tools.

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They have a tool for doc search, meaning

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searching the entire Microsoft Learn site, a tool

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for finding code samples, and a tool for

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fetching a specific Learn site.

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Right now, I have not given the tools.

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You can see I've commented them out here

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on purpose.

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That is to show what we can do

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with the tools and without the tools.

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So I am here, and if I go

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in and ask the question, make a –

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oh, I didn't show that.

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The instructions here are you are an expert

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in the C-Sharp version of Microsoft Agent

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Framework.

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Use tools to find your knowledge, and assume

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Azure OpenAI with API key is used.

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So a little like we do up here.

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And if we ask that without – we

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just add to LLM, which, by the way,

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is 4.1 nano.

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That was released about one and a half

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years before Microsoft Agent Framework came along.

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It will not know anything about what this

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is.

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But if we say make an example on

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how to make an agent, it will not

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say I do not know.

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It will come back and say it's this

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made-up nonsense.

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So it wants to use Windows Forms.

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It wants to use Newtonsoft.

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It do something with OpenAI here, and then

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it does all kinds of things that doesn't

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exist.

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It has just made stuff up trying to

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go to OpenAI.

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I have also seen it make some agent

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packages and so on.

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So if we start it again and try

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to ask the same question, it will come

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up with something new.

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Let me ask the same question again.

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So now it wants to use some COM

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import in order to make an AI agent

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trooper.

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This probably doesn't exist in the world, or

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if it does, it's certainly not what we

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want.

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So this is Hallucination's big style because it's

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in an area it doesn't know anything about.

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But if we give to the tool, which

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is essentially give it access to the entire

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Microsoft Learn portal, which of course also have

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Microsoft agent framework, among other things, it will

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become much better at this.

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Not perfect, but much better.

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So if we ask the same, make an

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example on how to make an agent.

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Let me make it big so we can

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see it better.

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It will now call the tool and look

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at the code and so on, and now

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it suddenly knows Microsoft agent framework.

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So it now knows it needs to use

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Azure OpenAI and stuff like that.

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It gets it from environment variables.

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We did it a bit different.

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And it's using not the API key, but

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now we can actually use it as a

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teaching experiment on how you instead use the

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role-based access control for Azure by simply

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just giving up the default.

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And the reason for this is that all

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the Microsoft samples use this, and they don't

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actually give a sample on how to get

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it with an API key because they don't

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want to have API keys rolling around in

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their samples.

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But beyond that, it gets an Azure client.

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It turns it into a chat client, and

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it says create agent, uses instructions and names,

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and do exactly as we have learned over

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the last few lectures.

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And then it gives links to where we

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can find information about this further on into

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the system.

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So that is the power of MCP, that

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we can, with just these few lines of

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code, have the entire system.

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Had Microsoft learned, had an API, we could

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have probably have built a lot of code

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and exposed that as a tool, but we

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don't need to because of MCP.

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GitHub in the same manner, and so on

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and so forth.

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MCP can do much, much more.

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Again, there's local tools for controlling browsers and

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stuff like that, but it's a bit beyond

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the scope of this introduction video at least.

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But all we do is we make our

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tools, and conveniently, those tools can be cast

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into those AI tools that we need down

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here.

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So very, very easy to do.

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One thing that are difficult to do right

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now is authentication against MCP servers.

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It's easy to do with API keys and

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stuff like that, but the entire OAuth part

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of it is very, very brand new in

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this package, so many of the OAuth options

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don't work as of this recording.

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But these open and free ones are very

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easy to use, as you can see.