I'm going to be covering the top five MCP servers that I

use for vibe coding.

MCP servers are a vital tool that you need to be using in

vibe coding in 2026 and if you don't know what an MCP

server is it stands for model context protocol and They are

servers that are programs that expose specific capabilities

to AI application through an interface Okay,

so there are three core features.

There's tools Resources and prompts but with that being

said I do want to show you guys The first MCP server that I

use in my real vibe coding workflow.

The first one is post hog So post hog is a data analytics

platform,

which I use to analyze traffic and data associated with

bridge mind AI So this is my website and I use post hog to

be able to analyze data So for example,

I can go to my dashboard here and let's go over to the

bridge mind website dashboard And I just started using a

post hog for bridge mind AI we launched like about two

weeks ago So what you can see here is that I integrated

post hog on Monday February 16th,

and I've been tracking analytics here So for example

yesterday four hundred and forty people went to the website

the day before that on Sunday 205 311 and then on Friday

four hundred and sixty nine But what I want to show you is

how I actually am using this Because what you can use is

you can be a human being right and you can go to post hog

and you can look at the Data and analytics,

but the thing about MCP servers is it gives your agent

access to all of that data And it's going to be able to not

only access the data that's in the post hog analytics But

it's also going to be able to cross reference that with

your code Okay,

and that's going to allow you to significantly improve your

conversion flows So I'll just show you the prompt that I

made here so I said I want you to use the post hog MCP

server to review the data and analytics associate with

bridge mind UI and Then I said review user analytics and

identify Improvements that we can make to our website to

maximize conversions based off of user behavior that you

see from the analytics Okay So what you're gonna see is

that all of this data in some of this isn't that great yet

because we haven't fully?

Integrated post hog for the past like 30 days, right?

It's only from February 16th and onward But what you can

see here is that top refers direct 3,865

website visits are direct, 2,813 from YouTube, 2,675

from Google, 358 from Twitter, and, you know,

95 from the app, right?

So it gives you a view of like, okay,

this is where your traffic's coming from.

But more importantly,

it also can help you improve your conversion funnel.

So literally,

it's able to look at your conversion funnel and say, okay,

here's what you're seeing.

Let's check out this one.

The pricing page,

13% of people that go to the pricing page actually select a

plan.

And then seven of those click the start free trial button,

right?

So you're seeing, okay, here's my conversion rate, right?

And now what's cool is that by using your AI agent,

you're able to improve your conversion funnel.

Okay.

So you can see all of this data and all of these

recommendations.

So it said, Hey, fix the pricing page.

There's 86% of people that drop off.

Okay.

So what we need to think through is, Hey,

how do we actually improve that conversion rate, right?

And the cool part is,

is that I can use my agent to be able to review the data,

review the analytics,

and then to be able to create a structured plan for

improving the conversion funnel.

So I'm going to switch over to Opus 4.6 max,

and I'm going to use bridge voice,

which is the voice to text tool that I use,

which offers near immediate transcription time.

So let's just use bridge voice real quick and prompt this

so that we can actually improve based off of these

recommendations from the post-hog MCP.

I want you to now review these findings and these

recommendations and create a structured plan for updates to

significantly improve our conversion funnel.

First review the analytics and even further depth,

and then review the code associated with those analytics

and those pages and create a structured plan that

implements best practices and implements improvements based

off of the actual data that you are seeing in post-hog so

that we can improve our conversion rate.

So I'm now going to change cursor into plan mode,

and I'm just going to submit this prompt.

And I'm not going to work through all of this in this

video, but I just wanted to be able to show you guys, okay,

post-hog MCP is a fantastic MCP server to be using in your

vibe coding workflow.

You can use this with cursor.

You can use with this with cloud code.

You can use this with codex,

but I'm just using it in cursor today as an example,

because it has a really nice UI.

But this is one MCP server that if you're not using,

this has significantly helped me improve my conversion

rate.

And every day as I get more data and more analytics,

I'm able to improve my conversion rate.

And the thing about this is that, hey,

before MCP servers and AI existed,

you would be implementing post-hog,

and then you would have to look at all of that data

manually.

And then you would have to update the code manually based

off of a strategy.

But now what we can do is we can actually just integrate AI

and automate the entire process.

So this is something that you definitely want to be doing

if you haven't already installed post-hog and are using

this MCP.

If you have a website, if you have an app,

you should be using this MCP.

I highly recommend it.

The next MCP server that I want to show you guys is the

Sentry MCP server.

So if you guys are familiar with Sentry,

Sentry is an application that you can hook up to your

application so that you can streamline your debugging

efforts.

So pretty much I connect Sentry to the BridgeMind API so

that whenever there are errors in production or issues in

the application, I get debugging alerts that basically say,

Hey, there's a 500 error or Hey,

there was a 400 error here.

You're going to want to fix this.

Here's the browser that the user was on.

Here's all the information that you need, right?

So what I use,

I use the Sentry MCP to be able to debug and then take that

and cross reference it with my API so that I can actually

solve these bugs as they occur.

So we can see here, as I said,

I want you to review the errors that you are seeing in the

BridgeMind API using the Sentry MCP and evaluate the errors

that we are getting in production.

Then create a structured list of your findings from what

you are seeing.

Do not update any code,

just review the errors and create a structured plan for

fixes.

I then put it in plan mode and I submit.

So here Sentry is running.

You can see that it's searching for events.

It's finding my organization.

It's going to be able to find these errors and you can see

that there are 13 tools enabled for Sentry.

So you can basically have who am I find organizations,

find team, find projects, find releases, get issue details,

search issues, search issue events.

So right now it's searching for issues in Sentry and you

can see that it's also counting error counts and events in

parallel.

And it's running all these tools at the same time.

And what this is going to do is it's going to find errors

that have been happening in the BridgeMind API.

And then it's going to be able to cross reference that with

the API because I dropped in that repo locally.

So it's going to be able to say, okay,

here's the error that I had in production.

Let's take a look at that error that we're experiencing.

And then let's look at the code and then it's going to

create a structured plan to fix that problem.

So this is what I use for errors and debugging any issues.

And I'm going to let that create its plan,

but definitely an MCP server that you want to be

integrating into your daily vibe coding workflow.

The next MCP server that I want to show you guys that I use

is the BridgeMind MCP server.

So this is an MCP server that I created for my daily vibe

coding workflow.

And this MCP server is officially going live into

production today.

We've gotten phenomenal feedback from early beta testers

and alpha testers.

And this MCP server is now live in production and I want to

show it to you guys.

So you can guys see here that I am using BridgeMind.

I have 49 tools enabled, four prompts enabled,

and four resources enabled.

And all I need to do,

and I'm going to show it with a really interesting example.

So I'm going to drop in the BridgeMind API.

I'm going to give it the following prompt and I'm going to

use BridgeVoice.

I want you to use the BridgeMind MCP,

and I want you to do an in-depth review of the BridgeMind

API here, and search in-depth for security vulnerabilities.

For each finding,

I want you to create a task with all of the instructions

and knowledge needed to complete that task to fix that

security vulnerability.

Launch as many sub-agents as you need to do a deep dive on

the code base and create all of these tasks inside of the

BridgeMind MCP,

and I want you to create it with the BridgeMind project

associated with my account.

So I'm gonna drop all of this in,

and what you guys are gonna see is it's going to be able to

launch a bunch of sub-agents,

and it's then going to create tasks in the BridgeMind MCP

to be able to then pass off to other agents.

And we're gonna ultimately end up using this to create

agent swarms,

and this is a phenomenal way where if you are working with

dozens of agents at the same time,

it's able to use the BridgeMind MCP to actually work at a

bunch of different tasks at the same time.

And I'm gonna show you guys this.

Let me actually open up,

let me log into my BridgeMind account,

and you guys are gonna be able to see this as it runs.

You can see that cursor is,

it said it found the BridgeMind project,

now it's launching a bunch of,

it's basically launching a security audit,

and then based off of the security audit,

it's going to be able to create all of these tasks.

And I'm gonna show you guys what this actually looks like

inside of the BridgeMind dashboard.

So check this out.

So it's working in the background,

and here you can see this is my BridgeMind account I just

logged in, and it says welcome back builder,

and here is my active project.

So I can click on this project, and as you guys see,

I have not used this project yet.

I just created it for this example,

so I'm gonna collapse this real quick.

But you have a really nice Kanban board here,

and what we're gonna see is that as this agent actually

works on this security audit,

it's going to then create tasks inside of the BridgeMind

app, which will be able to be tracked, updated,

and moved from status to status to status,

from to do to in progress, to interview,

to complete or to canceled,

based off of the agents that are working on them.

So this solves the context management issue that a lot of

people have.

If you guys didn't know, when you're working with agents,

as that context window gets more and further and further

and along,

if you're working with an agent that has 89% of its context

window filled, it's gonna be more prone to hallucination.

So what we've done with the BridgeMind MCP is we've created

an MCP that's able to create tasks that have the

instructions and the knowledge that are needed to create

that subtask that you can then pass off to individual

agents that will be able to complete that task on its own.

So rather than working on all of these tasks at the same

time, you're able to use one agent,

which essentially acts as the parent agent that creates the

task with two things,

the instructions and the knowledge that are needed to

complete that task.

It stores it in your Kanban board,

and then you're able to pass those tasks off to subagents

that have fresh context, fresh context windows,

and have all of the instructions, knowledge,

and resources that it needs to be able to create and

complete that particular task.

All right, so check this out, guys.

So this did just finish its audit,

and now it's actually creating the task.

So you can see ran create task in BridgeMind,

ran create task in BridgeMind.

So let's actually now pull up BridgeMind,

and let's refresh this so we get a look at it,

and check this out.

So now what we can see is that this is now saying, hey,

here's what we need to fix, right?

So it says, hey, here are the instructions,

and then here's the knowledge.

So what you can see is that in the instructions,

this basically creates a system prompt for that agent.

So rather than you writing the prompt yourself to fix a

particular issue or to complete a particular task,

you're basically passing off that part of task creation and

completion to the agent.

So it's the one that's doing the review,

and then it's writing the system prompt.

So this acts as a system prompt,

and then the knowledge here acts as the context.

You can see here that it has the file, which lines it's at,

what the code looks like, and what it needs to fix.

And then this is all that the agent is going to need to

then pass it off to another agent that's going to then take

this task and actually work in this process to be able to

move it to in progress to actually then write the code to

then pass it off to another agent for review that will

review the code and then mark it as complete.

So you guys can see here that this is working well.

And if we go back over to cursor,

you can see it's now created.

Look at that.

The first four were created and now it's continuing with

the remaining findings and creating more tasks.

So this is a phenomenal MCP.

So it just created eight tasks and it's going to continue.

So this is how we're going to be doing agent swarms and

bridge mind from now on.

You guys are going to be seeing me use the bridge mind MCP

daily in my live streams because, you know,

as you get further and further along, agent management,

agent orchestration is incredibly important in the bridge

mind MCP makes this that makes this job very,

very simple because you're basically managing agents that

are managing tasks that are passing them off to subagents,

which are passing them off to other agents.

So you create a complete to do process and status update

process that is very,

very simple and works very well in the agent orchestration

process.

So you guys are going to see me use this more.

You guys can go to bridge mind.ai and currently it is 50%

off for the pro plan and you get a seven day free trial.

So as soon as we get some more stable releases of

additional products, that price is going to go up.

So if you want to take advantage of that,

I highly recommend that you check it out today and go to

bridge mind.ai and check that out today.

There are instructions and documentation for how to

actually set up this MCP server.

It's very simple.

But with that being said,

let's move on to the next MCP server that I'm using daily

in my vibe coding workflow.

XA is a phenomenal MCP server that I use to provide ultra

powerful searches inside of my agent.

Okay.

So XA here, you can see it has three tools, two prompts,

and one resources enabled.

And what this is really good for,

for is fetching real time information.

So this is better than your out of the box web search that

you get from like Claude or cursor or codec.

So watch this,

I want you to do an in depth review of my Stripe

integration and review the version of Stripe that I'm

using.

I then want you to use XA to search the latest information

and documentation to make sure that everything about our

Stripe strategy and our Stripe implementation is

implementation is up to date.

Use XA to search the internet for up to date information

related to the actual version that we're using and confirm

that we are doing everything correctly.

If you have any findings, output them to me.

But first review our code, review our Stripe integration,

and then use XA to search and provide up to date

information related to our Stripe integration.

So this is like for an example of how I'm using XA.

So I use the XMCP to search the latest information on the

web.

Like I said,

it's better than your out of the box web search from

cursor, Claude, codecs.

You're going to want to hook this up.

It's completely free.

It's very powerful.

And I highly suggest that you use it.

So this is definitely a great thing to look at.

You can see that right now it's going to look at my Stripe

integration and then it's going to be able to use XA to be

able to perform more powerful searches.

And even if we go to XA, like let's actually check out XA.

So let's go to XMCP and let's go here.

So this is what they actually say.

So XMCP, so the web search MCP,

so complete setup guide for XMCP server.

So you can connect Claude desktop cursor, VS code,

and 10 plus AI assistance to X's web search and code search

capabilities tools.

So like, look at this, here's one of their tools.

So web search advanced XA.

So it's advanced web search with full control over filters,

domains, dates, and content options.

So like one of the biggest issues with AI is like,

you'll be talking to Gemini 3.1 pro, right?

And it's knowledge cutoff date is literally like January of

2025.

So sometimes when you're using these models out of the box,

unless they have an MCP server, that's like, Oh,

by the way, it's not 2025.

It's actually 2026, right?

Like when you're using XA out of the box,

it's going to be able to perform real time,

like up to date searches.

Sometimes when you're using some of these models,

it'll be looking for information that's like way in the

past, right?

So by using XA,

it basically enables you to provide the most advanced web

searches.

And you can see now it is now running those web searches,

you can see running web search XA and XA.

So this is definitely something that you want to use.

I I'm going to work with this,

but something that I use daily,

something that you definitely want to check out.

Again, it's free to set up.

I highly recommend using it.

I use it daily.

Definitely something like even this here,

search exit for Stripe webhook best practices 2026.

Right?

So like it uses 2026.

Like, Hey, just as a reminder, it's 2026.

Right?

So definitely something you want to use.

And with that being said,

let's move on to the last MCP tool.

Context seven is an MCP server that provides up to date

code documentation for LLMs and AI code editors.

So this kind of goes hand in hand with XA because what

context seven does is it allows you to fetch up to date

code documentation.

Right?

So like I said, Hey, you know,

if you're going out of the box, right?

And let's, you know,

use a similar example to what we just used, which is, Hey,

let's say I'm using the bird's mind API, right?

If I'm setting up a Stripe integration and I'm setting it

up out of the box,

unless I tell the AI assistant to be able to set it up with

a particular version of Stripe,

it's going to go with some outdated version from 2025

because that's the version that the model was actually

trained on.

So by using context seven,

it's able to fetch up to date documentation.

So watch this.

I want you to review which Stripe API version I'm using and

use the context seven MCP server to fetch the latest

documentation for this version.

I then want you to review the Stripe version that we're

using and making sure that we're implementing it properly.

Identify any findings that do not match up with the

documentation that you find.

So what this is able to do is that, hey,

every time that you're using one of these MCP servers

that's providing up-to-date documentation or advanced web

search capabilities,

you're going to improve your AI tool use that much further,

right?

Every edge that you can get, you want to use.

So if you're not using MCP servers,

you really need to start using them.

I use them daily in my vibe coding workflows and you guys

are going to start meet to see me using them a lot more

because hey, at the end of the day, as an AI engineer,

as a vibe coder, whatever you call yourself,

agent orchestrator,

the more tools that you can use that will give you an edge

are going to allow you to get that much further.

So if you're using context seven MCP out of the box,

it's going to provide up-to-date code documentation and it

will perform better out of the box than if you just

prompted an AI tool to be able to tell you like, hey,

I want you to build a Stripe integration.

So it says resolve library ID and context seven.

So it's going to be able to use this tool to be able to

fetch the latest documentation and then reference it back

to my birds mind API to be able to take a look at, hey,

let's make sure that this is up-to-date with the

documentation that we're seeing with that Stripe

configuration and API version.

And if you're not using this,

you absolutely want to start using it because like I said,

if you don't look at this,

so Cori docs is another tools right now,

it's querying the docs to take a look at that.

And it's doing that again,

it's looking at the start period, end period,

the subscription.

So it's doing all these things that are very, look at that.

So it says,

now let me look at the change log for the specific 2026.108

version.

So it literally knew what version I had,

it's querying the docs for that version.

And yeah, I mean, you really couldn't,

it would be a harder time,

you'd have a harder time doing this out of the box.

If you weren't using contact seven.

So start using post-hog MCP, start using Sentry MCP,

start using the BridgeMind MCP,

start using Exa MCP and start using contact seven because

these MCP servers will give you an edge and as AI agents

and capabilities get better,

using any edge is going to get you that much further.

So with that being said, I'm gonna wrap up the video here.

If you guys have not already liked,

subscribed or joined the discord community,

there's gonna be a link to the discord in the pinned

comment in the description and in the comments.

And with that being said,

I will see you guys in the future.