If you are using CPS or want to learn how to use them, this new MCP toolkit developed by Docker will
save you a lot of time and make it much easier.
It's really impressive.
And in this video I'm going to show you exactly how this works and how to use it.
MCP stands for Model Context Protocol.
It's an open standard created by anthropic that helps AI models talk to real world tools like calendars,
CRM, emails, or your local files.
So basically, instead of building custom connectors, every time you want to give you a access to something,
you can use MCP as a shared language between models and tools.
So MCP solves that by acting like a bridge.
Once you set up your model, can read emails, write code, update CRM, or fetch live data all securely,
and you can do all those things from one app.
Now, while MCP is a powerful concept and you can already use it for a lot of useful things and use
cases.
It's still early days, so the ecosystem is kind of messy right now.
There are a lot of apps and tools to choose from, but not much guidance.
Many MCP servers are open source, so you can find them on GitHub, but they require manual setup.
So normally you would need to go to GitHub.
Find the right repository for the MCP you want to use, and then set everything yourself.
And that includes downloading the code, managing dependencies, and in some cases even hosting the
service on your own machine and connecting llms to tools like Cloud Desktop App or Visual Studio Code,
or even a simple API takes a lot of manual setup.
So you need to know how to set up environment variables, credentials, permissions, and so on.
And because of that, if you are just starting out and you don't have any programming background, It's
tough to know which MCP servers you can trust.
A lot of people end up relying on random blog posts, GitHub threads, or community lists and hope the
setup will work and that nothing shady is inside the repo.
Yes, so the setup process is usually pretty manual, so you often need to clone the code, install
dependencies, and figure out how to run these services locally.
And when you are running tools that can access your machine, that can become a problem at some point
because security is one of the biggest concerns here.
So many of these tools have wide access to your system, and credentials are sometimes passed in plain
text.
So that means it's possible for sensitive information like environment variables, API keys to be exposed.
And if you are working in a team, it's even harder to use because most setups don't come with basic
protections like permissions controls.
And that's a big reason why adoption has been slow, especially on the enterprise level.
Also, every time you try to install one of these MSPs and it fails, it often still sends API requests.
So at the end, you might get a lot of errors and spend money for each API call.
So yes, it can be really frustrating.
And that's where Docker comes in.
Just to give you a bit of context, Docker is a really useful tool that lets developers run apps in
isolated environments called containers.
So it's widely used in programming and DevOps.
And honestly, I could make a whole separate course just on Docker itself.
So instead of manually setting up your own server and figuring out how to set up all this technical
stuff, you can now launch verified MCP servers in separate containers with just a couple of clicks
from Docker Desktop.
Docker desktop helps you run these MCP Servers safely without messing with your system setup.
So what that means is you can access all these MCP tools created by developers.
And Docker released this toolkit where you can see a whole list of MCP servers.
And these are all secured verified servers that you can access.
And you can connect these MCC to apps like cloud desktop app cursor, Visual Studio Code.
So to the MCP clients and automate a lot of tasks.
So I will show you exactly how to set this up and how it works step by step.
I will go through how to get started with Docker MCP toolkit, how to install it and launch your first
server, and how to use some of the tools on real examples.
So let's get started.
Obviously to start you will need Docker Desktop.
So go to docker.com and you should land on this page.
So simply download Docker Desktop on your operating system and install it.
Now, once you're done, please go ahead and open it.
Now, before just a few days ago, you had to open extensions in the left hand menu and search for MCP
toolkit.
As you can see, it has been deprecated and you have to use the integrated Docker MCP toolkit in Docker
Desktop 3.42 or later.
So Docker MCP toolkit is a Docker desktop extension allowing allowing to connect Dockerized MCP servers
to MCP clients.
Yes.
So a few days ago, the team integrated MCP toolkit into the user interface, and now it has a dedicated
tab, as you can see here.
Uh, it's still in beta, so you don't need to install this extension.
You can go straight to the MCP toolkit.
Now when you click on it.
It gives you a whole set of tools to easily install and manage verified MCP servers.
They have a catalog of nearly 120 MCP that are already set up, but I'm sure they will expand it soon.
All of these run in isolated Docker containers, so you don't have to worry about them accessing anything
on your system directly.
So as the first step is dedicated for servers.
The second one for MCP.
And the last one for clients.
So here you can connect all these MCP to apps like cloud desktop app, cursor or even some internal
custom apps.
All right.
So now let's connect it to a client.
So we are going to use Cloud Desktop app as our client as our MCP client.
So you just simply need to click here to connect and don't need to edit configuration file like we did
to connect the cloud desktop app to N810.
And as I said, this works with other tools like cursor or even your own local setup.
So you can browse and connect Dockerized MCP servers to your favorite MCP clients.
So as you can see, you have access to some of the very popular apps like GitHub, like notion, like
AWS, who can also give your agents access to MCP server like Azure.
You also got 11 apps.
You can use fire, which is really great to scrape the internet and Google Maps.
And when you scroll down, I'm sure you will be familiar with some of the apps.
We also have Shopify.
Slack.
Wolfram.
Wikipedia.
Webflow.
Now when you click on the specific MCP server.
Let's use Google Maps as an example.
Here we have an overview.
So this tool is for interacting with the Google Maps API.
And here you have more details such as links to repository.
And this is very important.
Available tools.
So here we can check what tools we can use for this specific MCP server.
So in Google Maps we've got maps directions.
To get directions between two points you have maps distance matrix to calculate travel distance and
time for multiple origins and destinations.
We also have maps, search places to search for, places using Google Places API.
And when you scroll down.
You have more details about the tools, which is really useful because by visiting this page.
An overview.
You can figure out what tools you would need to use for your specific use case.
Next, when you go to tools tab, here you have a short descriptions of the tools the SMTP server offers.
And then also very important configuration.
So here in that case we just only need to provide API keys.
Because to be able to use this server you have to provide API keys.
And I'm going to show you how to find API keys for some of the services like Google Maps, perplexity,
pickle and so on.
If you want, you can go to repository to check the GitHub.
And here you can read through the documentation to learn more about this particular Amqp server.
So if you are interested, you can learn in more detail how it works and how to configure it manually.
As you can see, this specific repo contains a collection of MCP servers.
So for example, let's open Google Maps.
And here we have some additional information.
Google maps MCP server.
For the Google Maps API we have tools.
Again you have setup if you'd like to learn how to set up this manually.
So you have JSON snippets.
And on the left hand side we have all the files.
So the code packages dependencies instructions and so on.
Yes.
So this MCP toolkit by Docker makes things so easy because the only thing you need to do is to for example
go to stripe.
Added to your MCP servers.
But in order to do that, you have to provide credentials.
So configure this MCP server.
But this is really simple.
You need to find API keys and that's it.
So go to configuration here.
Paste your API keys.
And it's all set up for you.
So you don't need to mess up with code and do everything manually.
So this tool is really great because it can save you a lot of time and money.
All right.
Now let's use Cloud Desktop App as our MCP client.
So once we install it go to Docker Desktop.
Launch it go to settings.
If you have never used Cloud Desktop app before you need to enable developer mode.
There should be an option to switch it on, then go to developer.
And here you should see all the integrations.
For now I've got just an A10.
So my cloud desktop app is connected to an A10.
And now when you go to Docker Desktop.
In the MCP toolkit, click on Clients Connect.
Now your MCP toolkit should be connected to Cloud Desktop app.
But before you will be able to see the connection inside Cloud Desktop app, you need to restart the
Cloud desktop app completely.
Just make sure to quit it.
And this is really important.
If you don't do that, it will not work.
Now open it again.
You can see that MCP Docker connection appeared.
So let's open it.
And just to confirm it's running now.
So this means that our MCP toolkit has been successfully connected to cloud desktop app.
Now, if for any reason your connection failed, just close the cloud desktop app, go to Docker Desktop.
Press on this button again and then restart the cloud desktop app.
And that's why Docker Desktop is so powerful, because you don't need to configure each MCP and each
tool individually.
You can simply connect all of them CP servers and the tools via Docker desktop and manage all of them
From this up.
All right.
Now, once our MCP toolkit is connected to the cloud desktop app, let's start configuring MCP.
So let's search for Google Maps.
Configuration.
And here we need to provide Google Maps API keys first before we start generating API keys and connecting
applications to the MCP toolkit.
Let's actually plan what we are going to do in the next part of this tutorial.
So let's add a few MCP from a catalog.
As our MCP servers.
Because you can combine multiple MCP to complete a single task to get much better results.
And that's why this is such a game changer.
So this is our task.
Let's say you are based in London and your remote team is mostly around Manchester.
You are planning a weekend meet up somewhere close to Manchester where you can all work together in
person.
We'll use Google Maps to find towns within 35 minutes driving distance from Manchester.
So when we search for Google Maps, MCP, the catalogue and go to tools.
We'll use two tools offered by the MCP server.
Let's use map search tool to find towns or areas nearby with coworking spaces or venues.
And also let's use maps distance matrix to calculate actual driving times from Manchester, including
traffic conditions.
You can also use other tools, for example maps directions to get directions between two points or maps.
Place details to get detailed information about a specific place.
But for this, we are going to use other MCP perplexity to make this our server and use its tools.
So then we can use perplexity MCP to research the pros and cons of each town, because we want to know
if it's affordable, is it to get to, and if it's a good place for entertainment or to relax after
work.
Specifically, we are going to use Perplexity research tool to perform deep research using perplexity
API and get a comprehensive research response.
So yes, you can do all these things in one conversation inside the cloud desktop app without switching
tabs, uh, or between websites.
So you just install servers you need connect them to cloud and then I can start using them.
So now I'm going to show you how to generate this API keys.
First we need to create a project on Google Cloud.
So search for console.
Cloud Google.
Open the first link.
Then login to your Google account.
Go to your console.
Now here you can create a new project.
So press on.
Create new project.
Give it a name.
Create.
Now just wait a moment, then select the project you just created.
And make sure you are in the right project.
Then what we need to do we need to enable APIs we want to use.
So in that case we want to use.
Let's check.
Two tools maps search places and maps distance matrix.
So let's search for it.
So I'm going to type maps search.
And this is the first result.
So places API.
So click on that.
Then we need to enable API.
So click enable.
So you'll be able to get detailed information about 100 million places.
Now let's copy the API key.
Let's go to Google Maps platform.
Here you can also restrict key.
I'm going to select maybe later.
Now when I go to APIs and services.
I can see all the tools I can use from Google Maps platform.
And when I scroll down.
I can see that places API is enabled because I can disable it right here.
Now we also want to Activate the Distance Matrix API to click on enable it.
If you want to calculate the travel time and distance for multiple destinations.
Alright, perfect.
Now let's go back to the Docker desktop.
And under configuration I'm going to remove this API key and creating one.
Let's paste the API keys we copied.
Confirm.
All right.
Perfect.
And now we should have access to this MCP in our cloud desktop app.
But we need to restart the app.
So let's do it.
And now every large language model offered by anthropic.
Should have access to this MCP.
So here you can switch between different large language models.
You have access to cloud sonnet for cloud opus for animal models.
And now when you press on this button you should see that you have access to MCP Docker.
And when you expand it.
These are all the tools that I connected in Docker desktop.
So all MCP servers with their tools are connected to cloud desktop app.
So here I have a file called Google Maps and Perplexity.
And I can easily switch on and off each tool separately.
So here we have our maps distance matrix And map search places where I.
Perfect.
Now let's actually give it a test.
So I'm going to open the cloud desktop app again.
And I'm going to ask it to use Google Maps tool to find out what cities near Manchester can I reach
within 35 minutes driving during evening rush hour traffic?
Let's send it.
And let's see what happens.
So I will help you find.
Okay, so now cloud is asking about permission to use this MCP server.
So as you can see maps search places MCP Docker.
So I'm going to allow once.
Let me search for nearby places and then check driving times.
Okay.
Now it's going to use this MCP server again.
So this time I'm going to allow always.
So you don't need to give it permission every time.
Now cloud is asking for the permission to use our second tool.
So maps distance matrix from this MCP server.
Okay I'm going to allow always.
Okay.
Now let's wait a moment.
Perfect.
Now we got results.
Here you can see the entire process of performing this search.
So I will help you find cities in Manchester that are reachable within 35 minutes during rush hour.
Let me search for nearby places and then check driving times during typical rush hour conditions.
And here you can see that cloud was using Maps Places tool from the Google Maps.
And you can also expand it to see the request.
You can see the response.
Right.
Great.
Then let me search for more specific cities and towns around Manchester.
It was using map search places tool three times.
Okay, great.
And then now let me check driving times from Manchester to these nearby cities during evening rush hour.
I will use the distance matrix to get multiple destinations at once.
And here it was using the second tool.
So maps distance matrix.
Let's let's expand it more Of driving college in Manchester, UK.
Destinations.
Okay, so it's found quite a few cities based on my search using Google Maps data.
Here are the cities and towns in Manchester that you can reach within 35 minutes of driving during typical
traffic conditions.
And here you have the list of the cities.
All right.
Just outside the 35 minute range.
Please note that these times are based on current traffic data and may vary during actual evening rush
hour.
Typically 5 to 7 p.m. during heavy rush hour traffic.
Some of these journeys could take longer, particularly those involving major motorways like right.
For the most accurate real time estimates during your specific travel time, I would recommend checking
Google Maps or similar navigation apps just before your journey.
As you can see, cloud was using current real time traffic data and the output is pretty detailed and
accurate in the second part of this task.
Now let's ask perplexity.
So use perplexity.
Let me just check.
Okay.
To research the pros and cons of each town.
Okay.
Let's just copy it.
And paste it here.
Now let's see.
I will use perplexity to research the pros and cons of each town.
Now it's gonna ask for permission.
Going to error.
Always.
I think it will take maximum two minutes, because perplexity is going to do a deep research.
Deepresearch.
Let's give it some time to process it.
All right, now let's check the response based on my research using perplexity.
Here are comprehensive analysis of the pros and cons of each town in Manchester.
Salford 70 minutes from Manchester.
Pros excellent transport links with frequent trams every ten minutes and direct Metrolink connections.
Cons most expensive for solo living utilities limited local options okay residence okay Stockport.
Good transport.
All right.
Outcome.
Very affordable.
Works and transport.
Limited.
Evening entertainment locally.
Chi Minh infrastructure.
Best local entertainment.
All right.
Summary.
Recommendations for affordability.
Bolton or Oldham offer the best value for quick commute.
33 minutes or 30 minutes, or fastest for entertainment or income has the best local scene Bolton for
students.
Nightlife nightlife best overall balance value offers good transport, moderate costs and reasonable
amenities.
Avoid budget conscious Salford and income are significantly more expensive.
The choice depends on your priorities, whether you value short commutes, local entertainment or keeping
costs low.
Perfect.
So we are able to get real time data from Google Maps using the Google Maps MCP.
The actual driving times, not just rough estimates.
Then we used one of the best AI search engines on the market to perplexity, to do deep research on
each location and all of that just by asking a single question inside the cloud app.
Now, this was just an example.
Now imagine how much time you could save when you start combining even more MCP servers and tools,
especially as Docker team the continuous verifying more of them.
All right, now I'm going to show you how to generate API keys in perplexity so you can set up perplexity
as your MCP server.
So first go to perplexity comm.
If you haven't used perplexity before, just for the context, it's one of the best AI powered search
engines.
Right now on the market, it takes your question, searches the web in real time, and then gives you
a clear, concise answer.
Usually the answer is backed by resources.
You can click on verify.
Also, it doesn't hallucinate as much as other llms.
So the perplexity AI is an advanced AI powered web search engine designed to provide accurate, trusted
and real time answers to user to user questions by combining large language models with live internet
search.
It uses sophisticated natural language processing to understand queries contextually, and then searches
authoritative online sources to synthesize concise, human like responses, complete with citations
to the original sources for verification.
Founded in August 2022, perplexity AI has quickly grown into a significant player in the AI search
space valued at around $14 billion as of mid 2025, with a user base processing tens of millions of
queries daily.
The company offers a free version and paid subscriptions, which unlock more advanced AI models and
features such as multimodal inputs, image documents, follow up questions, capabilities and enhanced
search depth.
And the key features conversational search so allows users to ask follow up questions and maintain context
within a session, making it more interactive than traditional search engines.
Return data access.
Unlike many AI models limited to static training data, perplexity assesses live web data enabling app
enabling up to date answers including live sports scores, election results and news events to search
modes.
Quick search for fast, straightforward answers, plus search for deeper, more tailored responses that
may involve clarifying questions.
All right, how it works.
It uses a blend of proprietary and third party llms, including GPT four.
GPT three and its own sonar model to interpret queries, retrieve relevant information from the web,
and generate coherent summaries.
It continuously crawls and indexes web content to keep its knowledge base current.
In use cases, perplexity AI is used for research, content summarization, language translation, data
analysis, and general information retrieval across various industries.
It is especially valued for providing verifiable, up to date information quickly and efficiently.
In summary, perplexity is a next generation AI search engine that combines conversational AI with real
time web search to deliver accurate source answers, helping users explore and verify information more
efficiently than traditional search engines or standalone AI chatbots.
Perplexity is very powerful.
I personally prefer to use it to ask question to search the web instead of going to ChatGPT or cloth
and ask the models to get an answer?
Yes.
So I usually go to perplexity first when I have a question, because it pulls real time info from the
web so you can get more current and accurate responses than you would from ChatGPT or cloth.
Even if you are using the search web features also without the extra fluff.
So in order to connect perplexity to MCP toolkit in Docker Desktop, let's go to Perplexity Comm.
Create your account.
I'm going to sign in.
Then go to your account at the bottom left corner.
Click on account.
API keys.
But before you will be able to generate your API keys, you have to top up your account.
Then create key.
Copy it.
Go back to Docker Desktop.
Go to catalog.
Search for perplexity.
Go to configuration.
I'm going to delete the API keys I already have and create new one.
Paste your perplexity API key here and confirm.
Great!
And now when you go to Cloud Desktop app.
And go to tools.
In the MCP Docker you should be able to see three tools from perplexity.
So perplexity ask perplexity, reason and perplexity research.
So these are exactly the same tools.
You can see here.
So now you are able to use perplexity inside Cloud desktop app.
Now just to let you know, using perplexity research is quite expensive because it uses deep research
to find relevant information for for your questions.
So just keep it in mind.
Now I'm going to show you how to connect another popular tool if I recall.
So it's kind of like perplexity.
But instead of giving you answers, it scrapes retail websites and pulls and pulls out raw data.
So perplexity gives you ready answers based on data, while five crore gives you data to work with.
So let's go to File Crawl.
As you can see, this is the fast, reliable web scraper for LMS, you can power your AI apps with clean
data cloud from any website.
It's also open source, the same as N810.
You can start for free with 500 credits.
It's trusted by the top companies.
As you can see, you can add it to m.c.p.s.
All right, so let's create an account.
Sign up.
Provide email and password and then login.
I'm going to login because I already have an account.
Then simply go to API keys.
Here you can create your API key.
So give it a name for example Docker desktop and create.
Copy.
Go to Docker desktop.
Search for file crawl.
Go to configuration tab.
Go to secrets.
I'm going to remove the current API key and create new one just to demonstrate to you and confirm save.
And that's it.
It should be set up and you should be able to use it in your Google Cloud desktop.
Actually let's check and you should have access to it.
Tools.
You can read the descriptions.
Go to your desktop app.
Let's check tools.
Mocp.
Docker.
And as you can see now I can use all of the tools.
All right.
Perfect.
All right.
That's it.
For this tutorial you learned how to use how to combine tools like Google Maps, perplexity and through
MCP toolkit in in Docker and how how you can use it in cloud desktop app and how easy it is to build
something useful.
I strongly recommend you using MCP Toolkit in Docker Desktop because it can save you a lot of time,
and also it can open a lot of possibilities, especially as more verified MCP get added over time.
I hope this was helpful.
Thanks for watching and see you in the next one.