शैडोइंग अभ्यास: Running AI Agents in Secure Sandboxes with E2B & Docker MCP | Docker’s AI Guide to the Galaxy - वीडियो के साथ अंग्रेजी बोलना सीखें

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Hi there, welcome to the next episode of AI Guide to the Galaxy.

My name is Olek and I work with the DevRel team at Docker.

Today we are in the real actual studio.

We are here at the Docker Captain Summit in Istanbul.

And it is my honor to introduce my next guest, who is a Docker captain, Jonas from E2B.

Hi, how are you doing?

Good, thank you.

It's great to be here.

It's been two days of very productive conversations about Docker, Docker products, roadmaps

and we're taking this chance to record this video face -to -face.

We'll see how it goes.

Leave it a comment if you think this is a great idea and we should do it more often.

So, recently, E2B and Docker announced this partnership.

And, well, our viewers mostly are familiar with Docker and Docker products.

So maybe, can you tell me a little bit about what E2B is and what do you offer?

So, E2B is an open -source infrastructure for AI sandboxes.

So if you want to run agents

that need access to like a full operating system and you want to do that securely and sandbox and isolate it, that's what E2B is for.

Right.

Sandboxes are a very hot topic nowadays.

Everyone is doing them from Cloudflare to all the coding assistant

shipping some sort of guardrails in form of seed belt or mangos and stuff like that.

So E2B, is E2B like a local sandbox, or is it the cloud machines?

It's cloud -based, and it's full virtual machines.

So the agent can get full access to a full Linux VM, and it's all in the cloud.

So you can also scale up like thousands of sandboxes in front of there.

That is awesome.

I can imagine the effort that went into creating the infrastructure of that.

Definitely not easy.

This is very, very cool.

So ETV provides the sandboxes and, well, Docker has a number of initiatives.

Most notably for this partnership was the MCP catalog,

the trusted catalog of MCP servers that you can plug and use from your AI assistants.

And maybe the supplementing technologies like MCP toolkit and the MCP gateway.

So can you maybe explain the partnership and what the integration is in a few words?

Yeah.

So with a partnership, Docker has this amazing catalog of like pre -configured MCP servers with like all the configuration you need.

And with the partnership, we bring the MCP servers that are already trusted and in the catalog to E2B sandboxes.

So when you run an agent in a sandbox, the agent has like automatic access to all of those 200 MCP servers.

Right.

Awesome.

When you say when you run a sandbox, what does it mean?

Can you maybe show an example?

How do I, as a developer or as a person running my agent, how do you create the sandboxes?

What's the experience look like?

So usually you would create a sandbox through an SDK that's either JavaScript or Python.

And then when you create a sandbox, which is just sandbox .create here, you can configure a few different MCP servers.

So here, this is fully typed.

You could, for example, do EXA, which is a search engine kind of, And then also the configuration is typed and you can provide,

for example, the API key for that.

Right.

So Docker has this catalog of MCP servers,

right, which are technically just Docker images with software that is an MCP server running inside them.

And there is a, like, surrounded technology, which is in case of headless machines is the MCP gateway Docker image

that acts as a configuration entry point in the proxy.

to the MCP servers.

So when I provide this configuration, so this is the API to create sandboxes with E2B.

When I provide this configuration, the library, the E2B library will spin up the gateway within the sandbox.

Yes, that is correct.

Is it like completely within the sandbox or is it an external...?

Yeah, the gateway runs completely in the sandbox, so isolated in that.

And then the MCP servers also run in the same sandbox.

Okay.

And the gateway is also accessible to the outside if you want, like authenticated, of course.

So if you have an agent running locally, it could use the isolated MCP servers in a sandbox as well.

Right.

Okadoke.

So let's look at this.

Walk me through this example more.

So we configure in sandbox and we create this.

So that will send the commands to the cloud ETB premises

and give me a virtual machine and the connection to

that right yeah and this because we configured mcp this will also automatically start the gateway

and like pre -pull the docker images for example for those mcp servers this is very interesting actually

so the docker catalog is just a number of um mcp catalog sorry those are docker images

and then uh they don't have any particular configuration externally

because it's the catalog resides and is sort of managed by the toolkit

or the mcp gateway uh

which well you configure them either from the user experiences like form

or using environment properties

and docker secrets uh in the in the in the catalog for in the gateway form like

when you just turn on containers uh how do you get the api like

that did you create it manually or uh so we take the catalog

which is like a huge yml file and then auto generate the types of

that and then in the background we map it back to the catalog

so what actually gets used in the end is the catalog right

but the catalog is quite complex

and like in docker desktop it's also mapped to like a nicer ui

and here we just map it to a different oh

that is awesome so but it's a one -to -one mapping in the end right

so like you get the api for both javascript and python uh

sort of for the price of one yeah yeah

so we just take the catalog and then auto generate everything

that is awesome okay and i can see you put entropic api key

so we're gonna use cloud yes

so here we just run cloud like the actual cloud code inside the sandbox

and we add the mcp gateway here the first command so

when you do sandbox .command .run this actually runs like a command in the sandbox

sort of like docker exec yeah but in the for the sandbox okay um

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and then we can start i need to wrap here um we then start cloud with the task here

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and the yolo mode because we're in a sandbox and we don't really, yes.

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It cannot mess up our machine.

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And in this case, we have a very simple use case where we just search for interesting research papers

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and then summarize it and turn it into, like, a wide -coded summary in, like, an HTML page.

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And then, because, again, we're in the sandbox, we can really do stuff we wouldn't do on our laptop.

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We can expose it as an HTTP server here and, like, host a website.

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I can run that.

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so i hope that actually works

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so this will probably take however long cloud decides to do its research right okay

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so it created the mcp gateway yes and it prints the url for us

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so yes so so for example

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if you have cloud desktop running you could also connect your

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cloud desktop to the a remote sandbox with the gateway running inside of it.

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Right, right.

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I will need to provide the authorization token, but like I can create, come on, connect to that from external things.

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Okay, so now what is happening?

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So now Claude is processing our request and we configured the MCP gateway.

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So it has access to tools from the servers that we configured, which is the Archive and...

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Archive and DuckDuckGo.

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DuckDuckGo just to have a sad engine really right

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and then it will use those servers

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and generate on us some information in the index hml page

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and then we can access that

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because we spin up um yeah interactively a python server yeah and that's of course something you would not really

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usually want to do this is the demo purposes uh demo so uh you would probably make it

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make your clod write it to the database

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and then you access it securely or put the files into your s3 bucket

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or anywhere else okay this takes a little bit of time uh can you tell me

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so here you have clod within the sandbox yes do you package clod by default

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or is it something that uh just accidentally works here yeah uh

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so when you create so sandboxes are created from templates

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and templates are really like the root file system of a of the virtual machine

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so you can create a new template

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and then install whatever you want in there

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so this is example code of how you create a template you can start from the mcp template

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which already has the gateway installed

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and a few tools like npm python is already installed in there and then you can extend it however you want.

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So we have, for example, apt install.

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So if there's, for example, if you want to install curl, you would just add curl here.

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Or if you want to do, if you want to clone a certain repository, you could do that here as well.

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And this is a template which is not the actual instance of the sandbox, but this is the file system.

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Yes sort of projection yes so it will be used yeah we're starting the sandbox

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and each template has a name and then

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when you create the actual sandbox you just reference that name

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and it's based on that so in this example everything would have curl installed

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or if you do the right so in sort of

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an analog in the docker universe terms this would be like

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sort of building a docker image yes except specifying the entry point

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because the sandbox entry point is probably controlled by correct yeah okay

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and there's also start commands which is kind of like an entry point

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so if you have a service

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that you want to start automatically you can also do

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that okay but this is very similar to docker image

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and we even have support to use docker images as templates oh you can create an etb .docker file usually

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and then this is converted to a template as well do you like the the api

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or docker files more for creating templates the api

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because it's better for like programmatic access So if you have a use case where you provide coding agents for your users,

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for example, programmatic is usually the better way.

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Yeah, I agree.

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I agree.

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I have experience with test containers.

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So it's a very similar story there, which it's an open source library,

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and they expose programmatic API to configure and manage containers within Docker context.

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So I can totally see the appeal of running the API.

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Right, so we have the results from Claude.

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So you can see it found an interesting paper, Foundations of Large Language Models.

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Okay.

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And then also did some research about the authors.

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And then hopefully if it worked, published it at this URL.

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I think it says sandbox closed successfully.

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Yeah, okay.

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We were too slow.

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The sandbox had a lifetime of five minutes and we talked too long.

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So it's already gone.

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uh but i can run it again

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if you want no you don't have let's let's run let

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okay let's show it we're gonna edit it in post yeah uh no uh

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so i believe you

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that it works i actually have seen it work i've built

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a couple of examples uh i've mostly tried python myself to figure out pieces

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which you know because you help me debug issues there but

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so i i know that it works

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and i know you can expose those uh sandboxes uh over the internet

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if you want to like interactively sort of look uh for the demos

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so you said you're not really you won't do this um during the normal

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like usage of sandboxes um well like

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if you can share some details like what is the common patterns how people use EGB sandboxes.

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Is it common to package AI systems within the sandbox

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and run it as a sort of isolated cloud machine for the unit of computation

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or do people connect from external AI systems?

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What do you see happening and also what do you personally think is a more interesting way going forward?

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So I think one of the most common use cases is like the true coding agents

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that you want to run completely in the background

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so for example if you have like if you've seen cursor backbot which like

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partially runs code or like rabbit which like um does pull request reviews

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and like fixes code already um then usually like the agents run actually completely in the sandbox

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just to have it fully isolated and

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but of course there's also benefits to do it like partially in the sandbox partially outside

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because um well it's it's a bit easier to orchestrate probably

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if you run partially outside um

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and i didn't quite understand what you meant with the no interesting so

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if you look at the home page for etb yeah uh

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well it's like there is a lot of examples uh here for technologies

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that you can connect if you scroll a little bit down right

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so we have uh there were some here for example right

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and i understand that those could be synthetic examples but

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if you click on the open ai for example right

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so here the

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which i assume is a classic example you run open ai externally in your in your python code

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and then you connect it to sandbox just to run the code oh yeah

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that is a very common use case as well for example

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a lot of the chat applications have some way of running code right like

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if you give it a csv file you like figure out

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how many columns i have in there they write python code

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and then actually run the python code

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and then of course only like the actual code execution is in the sandbox right

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and very short -lived usually and this is like a major use case Um, and you can, yeah, I, yeah.

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Right.

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So what I hear is there is no particular preference, uh, from the sort of, uh, user point of view, like if they want to connect external clients, it's absolutely fine.

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If they want to put it into the sandboxes and have it to run that more like independent, longer, uh, end -to -end processes, that is also all good

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and fine i think it also depends on who what do you want to isolate

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and what do you want to like protect against

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because in the end like the sandboxes provide a lot of

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isolation right yeah this is very very cool i'm very very

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happy uh with the was was how this partnership turned out it's really easy to configure the mcp servers um

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so i know that docker uh mcp toolkit recently added uh the remote server abilities

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so like if you can connect to for example notion uh server

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and from idea token uh but the notion server is not run locally in the container

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but it just connects to notion api uh would

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that work with this uh with the integration like this as well

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that is already supported

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so you can already for example notion is a remote one uh you can connect it like this

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but for now mostly pre -configured ones so those that are actually in the catalog you can use

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right okay okay we can also now see the actual demo

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result okay it's just real oh no we went too fast

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you probably need to increase the time out somewhere in the code just say it say

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that like run it like for 10 minutes or something yeah right okay

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so you can do remote uh a lot of mcp servers

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uh are created i know with the sort of idea

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that their end users will be uh will be individual uh individuals who is their particular data access rights

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and there's this whole OAuth integration story for mcp servers uh how does

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that work or i assume there is not it's not important for programmatically created tasks um yeah

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so how does it

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so right now oauth doesn't work in the mcp gateway with

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e2b right i think docker has already some auth support for like two

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or three mcp servers as far as i know like a very little subset um

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but i do see that oauth is

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very important

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and then we will have to figure it out how also

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it fits into like the programmatic access use case yeah yeah

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and i don't think we can ignore it just

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because it's like a programmatic use case um

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because in the end this is like user data and the user needs to give access to that

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um for now it's just api keys yes so like in the docker toolkit there are some servers like for For example,

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Github that you can configure with OAuth, right?

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You can also configure it with the usual token, which is much, much simpler and maybe offers you more control for the integrations, because in the OAuth case,

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you really need to have a user in the loop and they need to review the OAuth consent screen and like,

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it makes no sense to show a consent screen if there is no end user present in the loop.

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You might as well go with the token

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and then the predefined rights uh

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so i see i like i honestly assume allows is not

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the most important feature for for the programmatic use cases like this um

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but specifically with remote servers most of them have some sort of allows i just realized

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that we have a sandbox skill in the demo so it would never work um

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the fourth trial see this is an example how easy you can change your code

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that runs this integration and how convenient it is to work with e2b sandboxes that actually

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if you think about it it's quite a sophisticated piece of

268

turtles all the way down we run some javascript code

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and it creates a virtual machine and then inside

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that virtual machine it runs docker engine i assume

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because it needs to run containers and it runs a container for mcp gateway

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and it needs to run the containers for individual mcp servers uh and all of that surprisingly works

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and at the same time surprisingly fast no it's actually pretty

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fast spinning up a container is fast i assume you have

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a lot of effort put into optimizing the startup for the sandboxes uh specifically

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because you mentioned the short -lived uh interactions with them as well um

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so this is all glorious

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and nice um uh are there any plans to work on

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other uh programming languages to support uh in the api

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or is javascript and python sort of the largest chunk of the ecosystem

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that you are aiming at currently i i'm this is not

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really my field like i i don't really work on the sdks but

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in ai right now i think javascript

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and python probably make up 99 of all use cases i would love to see go personally

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and i know that some customers actually build their own sdks for

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that yeah you have the sort of a rest api

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or something yeah you can you can use the api

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and yeah yeah the sdk is open source

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so you can also just like reverse engineer the sdk it's except for like the template template system it's not

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that complicated yeah

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so it would be fairly easy to for the basic operations

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like creating a sandbox you could just use the api this

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is an exercise for the curious watcher dropped the script from

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the javascript sdk also the entire um project is open source yeah

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so there's also like the open api specs for example right

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can i can i run the backend myself on my premises

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or yes you can it's it's not super easy to save for us because it's quite a lot of

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stuff involved to make it work um so it's not like a docker run and then

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i i think it's just the log file now oh yes okay um

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so we've got our vibe coded landing page here well

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that is quite awesome so you get the summary

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and you get the information about the authors and

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so the information about the authors what what the what was that was using the

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search engine yeah this is awesome this is very easy to

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use you can you can all i can ultimate those tasks i can put them in github actions

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and the only and the only thing

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that i need to configure to get access to the sandbox

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i just need the etb api key correct yeah uh

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and they will npm library or like a python library yeah okay this is awesome uh

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what is your favorite mcp server oh the catalog because you said

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that you're sort of parse the situation uh

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or what's your least favorite okay what is what is one

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that you hit with the most passion okay i need i need to think for

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that i think my most favorite one

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is probably dr go because it doesn't need an api key

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and i used it so much for testing okay um so

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and it always works like i never had a case where

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i mean it's a very simple mcp server there's one tool

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but it does its job

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so i love it perfect for testing yeah it's it's it's a perfect

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and i've probably used it like a thousand times in the

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last week the one i hate the most you don't have

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to answer we don't have to go on camera with this you can just tell me

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that it's at last and later oh actually it's it's probably the ones

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that need the most configuration yeah where there could be same defaults like i don't have a specific one

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but sometimes it's like you need 20 different fields you need to configure

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but you actually only need two

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and i think that's a pain yes yes i think so

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which is actually frankly that is the case i think with the atlassian mcp server

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that we have in the catalog

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because you need to have the key for maybe confluence

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and then jira and some urls for both of them

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and some additional configuration uh it's not

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so easy from the lick uh it's probably very convenient

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when you need to use it in anger in real life but like

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if you need to create a demo yeah uh you will you kind of stumble on this uh

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which is a minor use case it's not it's not actually like an actual complaint uh

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and sorry the docker hub mcp server i'm not just saying

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that because i'm a docker captain

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but i've used it a lot um to find documentation about other docker images right it's really good

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because you get the like true source of the documentation

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and not if use web search like you get a lot of wrong information and on dock hub it's usually right

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so yeah docker hub could be the source of information right very very good uh

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so how do people get started with e2b

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and maybe docker mcp catalog on e2b sandboxes

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and where can they maybe meet the community

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and ask questions to how to use this integration where do they go

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so if you want to get started with E2B in general, there's a very generous free tier.

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And if you want to try out MCP, there's a quick start guide with TypeScript and Python symbols that you can run just like that.

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And we also have a lot of examples in our cookbook.

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So for example, if you want to run cloud code or research agents or browser base for like web automation,

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like we have a lot of examples for that right and

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if you have questions there's a e2b discord

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that you can join i think that should also be referenced somewhere somewhere on the e2b page

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i'm sure it's uh somewhere there we're gonna find it

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and we're gonna put the links into description of the videos

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so header uh no thank you so much for joining us

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and explaining how it looks and what is it to be

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and how to use the sandboxes it was a pleasure stay tuned for the next episodes

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and please check out the etub and docker partnership

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and what you can do build uh running your agent securely in isolated sandboxes,

362

um, with enabled by default YOLO mode, which is fun thing to say.

363

Thank you so much.

364

See you there.

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यह C1 स्तर का स्पीकिंग पाठ वीडियो “Running AI Agents in Secure Sandboxes with E2B & Docker MCP” पर आधारित है। सबसे ज़्यादा दोहराए गए शब्द ये हैं: docker, mcp, sandbox, server, example। इस वीडियो में शैडोइंग के लिए 364 वाक्य और 4291 शब्द हैं। बोला गया हिस्सा 25:17 लंबा है। वक्ता लगभग 170 शब्द प्रति मिनट की स्वाभाविक गति से बोलता है, जो रोज़मर्रा की बातचीत के करीब है। केवल 79% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली कठिन है।

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वीडियो के 15 सबसे कठिन शब्द, उच्चारण और अर्थ के साथ:

शब्द	उच्चारण	अर्थ
catalogue संज्ञा	/ˈkæt.əˌlɔɡ/	सूची, तालिका
template संज्ञा	/ˈtɛm.plɪt/	साँचा, क़ालिब
container संज्ञा	/kənˈteɪ.nəɹ/	पात्र, डिब्बा
expose क्रिया	/ɪkˈspoʊz/	खोलना, उघाड़ना
authorization संज्ञा	/ˌɔːθəɹaɪˈzeɪʃən/	अनुज्ञा
premise संज्ञा	/ˈpɹɛm.ɪs/	आधार, पूर्वाधार
automobile संज्ञा	/ˈɔː.tə.məˌbil/	मोटरवाहन, गाड़ी
cookbook संज्ञा	/ˈkʊkˌbʊk/	पाक कला पुस्तक
discord संज्ञा	/ˈdɪskɔɹd/	कलह, फूट
spectacles संज्ञा	/ˈspɛktəkl̩z/	ऐनक, चश्मा
subset संज्ञा	/ˈsʌbˌsɛt/	उपसमुच्चय
mango संज्ञा	/ˈmæŋɡəʊ/	आम
reside क्रिया	/ɹɪˈzaɪd/	रहना, बसना
viewer संज्ञा	/ˈvju.ɚ/	दर्शक, ईक्षक
lick क्रिया	/lɪk/	चाटना

दोहराने लायक वाक्य

वीडियो के छोटे, पूरे वाक्य जिन्हें आप रोज़ की बातचीत में इस्तेमाल कर सकते हैं:

Hi, how are you doing?
We'll see how it goes.
When you say when you run a sandbox, what does it mean?
Can you maybe show an example?
What's the experience look like?

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचना	वीडियो में
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है	are already trusted · is typed · are created
Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारी	sandbox, which is · EXA, which is · right, which are
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है	It's been · have let · have seen

ध्यान देने योग्य उच्चारण

वक्ता 39 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे don't, we're, I'm। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

“th” की ध्वनियाँ: authorization /ˌɔːθəɹaɪˈzeɪʃən/, authenticate /ɔˈθɛn.tɪ.keɪt/, synthetic /sɪnˈθɛtɪk/
“sh” और “zh” की ध्वनियाँ: configuration /kənˌfɪɡ.əˈɹeɪ̯.ʃən/, authorization /ˌɔːθəɹaɪˈzeɪʃən/, documentation /ˌdɑkjəmɛnˈteɪʃən/, computation /ˌkɑmpjʊˈteɪʃn̩/, projection /pɹəˈd͡ʒɛkʃən/
लंबे शब्द — बलाघात सही रखें: configuration /kənˌfɪɡ.əˈɹeɪ̯.ʃən/, programmatic /ˌpɹəʊ.ɡɹəˈmæt.ɪk/, authorization /ˌɔːθəɹaɪˈzeɪʃən/, automobile /ˈɔː.tə.məˌbil/, documentation /ˌdɑkjəmɛnˈteɪʃən/

हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:

/v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: gateway /ˈɡeɪtˌweɪ/, watcher /ˈwɑ.t͡ʃɚ/, viewer /ˈvju.ɚ/, vibe /vaɪb/
/z/ — इसे “ज” (/dʒ/) न बनाएँ: expose /ɪkˈspoʊz/, authorization /ˌɔːθəɹaɪˈzeɪʃən/, surprisingly /səˈpɹaɪzɪŋli/, optimize /ˈɑptɪmaɪz/, repository /ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/
शब्द की शुरुआत में s + व्यंजन — पहले “इ” न जोड़ें: spectacles /ˈspɛktəkl̩z/, stumble /ˈstʌmbəl/, specify /ˈspɛs.əˌfaɪ/, startup /ˈstɑɹtˌʌp/, scroll /skɹoʊl/

इस वीडियो से अभ्यास कैसे करें

पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर catalogue, template, container जैसे शब्दों पर ध्यान दें।

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →

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इस वीडियो का व्याकरण

ध्यान देने योग्य उच्चारण

इस वीडियो से अभ्यास कैसे करें

शैडोइंग तकनीक क्या है?