Live Demo of GitHub MCP Server
Key Points
- Sam Marorrow (lead developer) and Toby Padilla (principal product manager) opened the session, introducing themselves and the GitHub MCP server demo.
- MCP (Model Control Protocol) enables LLMs to retrieve up‑to‑date or private context and to perform side‑effects such as creating files or modifying repositories, acting as a bridge between AI and the outside world.
- Originating from Anthropic’s November release, MCP standardizes function‑calling APIs; Anthropic’s reference servers—including the original GitHub MCP server—spurred community adoption.
- GitHub has taken ownership of the MCP server, rewritten it in Go for better performance, and the demo will showcase installing packages from the GitHub MCP registry into VS Code, interacting with GitHub Issues, and using a coding agent, with post‑talk follow‑up for additional questions.
Sections
- Live Demo of GitHub MCP Server - Sam Marorrow and Toby Padilla introduce the GitHub MCP server, outline a hands‑on demo and use‑case walkthrough, and invite post‑talk questions.
- Demo of MCP Agent Integration - The presenters highlight a newly launched open‑source MCP project that quickly became GitHub’s top repo, walk through installing its VS Code and VS Code Insiders hosts, and demonstrate the agent mode functionality despite intermittent service outages.
- AI-generated GitHub Issue Summaries - The speaker demonstrates how an AI agent can automatically create, summarize, and enrich GitHub pull‑request issues—including generating Mermaid diagrams—highlighting the platform’s powerful automation and visualization capabilities.
- AI‑Powered Mobile Coding Workflow - The speaker demonstrates how an AI‑driven MCP platform, using integrated coding and browser agents, can automatically create pull requests with before‑and‑after screenshots, be steered in real time, and even be operated from a mobile device to edit and refine personal websites on the fly.
- Introducing the MCP Server Registry - The speaker announces a new public registry of high‑quality MCP partner servers, previews upcoming self‑publishing via the OSS MCP registry, and encourages users to install the MCP server from GitHub and try its agent mode features.
Full Transcript
# Live Demo of GitHub MCP Server **Source:** [https://www.youtube.com/watch?v=LwqUp4Dc1mQ](https://www.youtube.com/watch?v=LwqUp4Dc1mQ) **Duration:** 00:15:03 ## Summary - Sam Marorrow (lead developer) and Toby Padilla (principal product manager) opened the session, introducing themselves and the GitHub MCP server demo. - MCP (Model Control Protocol) enables LLMs to retrieve up‑to‑date or private context and to perform side‑effects such as creating files or modifying repositories, acting as a bridge between AI and the outside world. - Originating from Anthropic’s November release, MCP standardizes function‑calling APIs; Anthropic’s reference servers—including the original GitHub MCP server—spurred community adoption. - GitHub has taken ownership of the MCP server, rewritten it in Go for better performance, and the demo will showcase installing packages from the GitHub MCP registry into VS Code, interacting with GitHub Issues, and using a coding agent, with post‑talk follow‑up for additional questions. ## Sections - [00:00:00](https://www.youtube.com/watch?v=LwqUp4Dc1mQ&t=0s) **Live Demo of GitHub MCP Server** - Sam Marorrow and Toby Padilla introduce the GitHub MCP server, outline a hands‑on demo and use‑case walkthrough, and invite post‑talk questions. - [00:03:09](https://www.youtube.com/watch?v=LwqUp4Dc1mQ&t=189s) **Demo of MCP Agent Integration** - The presenters highlight a newly launched open‑source MCP project that quickly became GitHub’s top repo, walk through installing its VS Code and VS Code Insiders hosts, and demonstrate the agent mode functionality despite intermittent service outages. - [00:07:05](https://www.youtube.com/watch?v=LwqUp4Dc1mQ&t=425s) **AI-generated GitHub Issue Summaries** - The speaker demonstrates how an AI agent can automatically create, summarize, and enrich GitHub pull‑request issues—including generating Mermaid diagrams—highlighting the platform’s powerful automation and visualization capabilities. - [00:10:27](https://www.youtube.com/watch?v=LwqUp4Dc1mQ&t=627s) **AI‑Powered Mobile Coding Workflow** - The speaker demonstrates how an AI‑driven MCP platform, using integrated coding and browser agents, can automatically create pull requests with before‑and‑after screenshots, be steered in real time, and even be operated from a mobile device to edit and refine personal websites on the fly. - [00:14:16](https://www.youtube.com/watch?v=LwqUp4Dc1mQ&t=856s) **Introducing the MCP Server Registry** - The speaker announces a new public registry of high‑quality MCP partner servers, previews upcoming self‑publishing via the OSS MCP registry, and encourages users to install the MCP server from GitHub and try its agent mode features. ## Full Transcript
All right. Well, um, welcome everyone to
hopefully a live demo of the GitHub MCP
server. I'm Sam Marorrow. I'm the lead
developer building GitHub's MCP server.
Worked at GitHub for about four years.
And as you can see, I love snow sports.
Um, and
>> hi, I'm Toby Padilla. I am a principal
product manager at GitHub, and I'm in
charge of our MCP initiatives, which
means the GitHub MCP server, the GitHub
MCP registry. I'm also a member of the
MCP steering committee working on the
open source MCP registry.
So, uh, firstly, I wanted to do a little
hands up. So, uh, hands up if you know
what an MCP server is. And now, keep
your hands up if you've ever used one.
a lot of hands and keep your hands up if
you've ever built one.
Oh, really? Awesome. You'll have to come
and talk to us after. I'd love to know
what you're building. Uh, so yeah,
firstly, Toby's just going to give a
little introduction of MCP and
particularly the GitHub MCP and what it
does. And then I'm going to go into a
demo and I'll show you kind of
installing from our registry into VS
Code. And then um I'll be working with
some GitHub issues and coding agent and
showing some fun stuff you can do. And
Toby's going to go through a few use
cases afterwards because 15 minutes is
not enough time to show everything we
can do. And uh we're not going to have
any time I'm afraid for Q&A. But if
anyone's got burning questions, we'll be
around after the talk. So please do come
up and let us know what your questions
are. Um, so Toby,
>> so what is MCP? And I think a lot of you
said that you're familiar with it, but
just briefly, MCP is a way for AI to
interact with the outside world. And
that primarily means two things. One is
that it can fetch context that the model
wasn't trained on. So this might be
information that was published after the
model's cut off training date, or it
could be information that was like
private if you had like internal
information that wasn't accessible to
the public web and the LLM got trained
on it. And secondly, it's a way for it
to interact with the outside world and
create side effects. So it could create
a file system or a file on your local
file system or a GitHub repo or a Figma
design. Um MCP is about 11 months old,
so it's not even a year old. Um
Anthropic created it last November. And
I like to say it was more of a social
innovation than a technical innovation
because there was pre-existing function
calling APIs, but they weren't getting a
lot of traction. So what Anthropic did
was create a standard around those APIs
um and then bootstrap the community with
30 high-quality reference servers
including the original GitHub MCP
server.
And this is a look at our MCP server. So
we've got a bunch of tools. Like I said,
Anthropic created the original one and
they told us it was the most popular of
the original set of MCP servers. So we
worked with them to take ownership of
the MCP server and we ended up rewriting
it and go because it was in Typescript
and we've launched it and it was quite
popular. We'll just talk through what it
does and and how it engaged with the
community.
Um, the week that we launched it, it was
actually the most popular open source
project on all of GitHub. So, it was
exciting to see that there was sort of
this pent-up demand to drive uh GitHub's
platform with agents.
And now I'll hand it over Sam so he can
show you what it does.
>> All right. So, somebody told me there's
some outages and things going on. So,
fingers crossed everything works. Uh so
firstly this is our MCP registry web
page and um I'm going to just install it
and
hopefully everything will work. You can
see that we have install for VS Code and
VS Code insiders. Um VS Code is actually
the most comprehensive MCP host that
exists. So it has the complete coverage
of the latest version of the spec. It
has more support for the MCP protocol
than any of anthropics hosts. And if you
use insiders, it's sort of the nightly
build for VS Code. And this is where
they're launching a lot of super
innovative MCP stuff. So if you're doing
MCP work, I would encourage you to get
VS Code insiders and test your MCP
servers in there.
Okay. So I should be assuming the
authentication completes successfully.
Yeah, I think I'm logged in now.
It's going slow. So I think the outage
is affecting stuff slightly but not
enough to actually stop me. So
uh firstly let's actually just give
stuff a go and see what happens.
So um uh some of you are probably
already familiar but um this is the
agent mode tab and I'll make it full
screen so it's easier to see. And
firstly I'll just try a super simple
prompt. can you list some issues from a
repo in my um account?
And you can see it immediately ran the
list issues from our MCP server. And
because I didn't ask it to do anything
with that information, it's just listing
them out. Um and um it showed me the
closed ones, too. That's cool. Uh MCP
also has a really interesting feature
called prompts which is like a pre-baked
prompts and um
uh if you want to enable a more complex
agentic kind of workflow from a single
command, they're like slash commands. So
um this one assigned coding agent. It
asks me for the repository I wanted to
work on and then it generates a prompt.
And this is our MCP server providing
that. And now it's just going to go
through a list of issues from the
repository
and it's going to decide uh like which
ones it thinks an agent can work on and
then it's just going to assign coding
agents. So, I'm going to allow it uh for
this session
and um
we'll have to give it a moment, but uh
it should hopefully assign a few issues
and um
yeah, like it it decided that some of
the issues aren't worth assigning and
that's good. That's that's kind of what
the prompt was intended to do. So
ideally lowquality issues and things
that needs further specification don't
get triggered. So anyway, uh that's the
MCP prompt and I do think that's pretty
cool. The um
for a slightly more fun one, let's try
aggregating
information from the GitHub MCP server
repo. So for this prompt, we're going to
get it to pull down recent pull requests
and then generate an issue celebrating
the work that was done in them. Um, so
as you can see, it immediately listed
the pull requests from the correct repo.
And now it's just processing the
information. And in a moment, it'll ask
me uh to let it uh open an issue for me.
Um,
I spend most of my life obviously
waiting for agent modes to run. Um, but
um,
all right. Uh, and now it's going to
summarize it, but it's already created
the issue. It's already done that. So,
if I skip into my web browser, I should
be able to
have a quick look and blah blah blah.
So, um, yeah, I'd asked it to summarize
the pull request and to generate a bunch
of mermaid charts. And, um, I don't
know. I like every time I see this, it
blows my mind. It's kind of,
uh,
from very basic prompts, it's able to
generate some really advanced things. So
if you're interested in um like
improving your issue bodies and things
like that and doing more summary work,
especially for managers who think why
would I touch this technology? I think
like you know this is just a oneshot
short prompt and you can see the kind of
really interesting things it's come out
with. Um and if you were to iterate on
it and kind of refine things, there's
all sorts of things you could create.
So, um, yeah. Anyway, that amazes me
every single time.
>> I think it shows off GitHub's ability to
render mermaid charts as well. Like, I
don't think I knew that it did that
until I saw the MCP server go ahead and
do that. I was like, "Oh, wow. There's
this rich capability in our platform
that the MCP server helps you find just
because it would be way too much work as
an individual to do it. But when you let
the LLM do that hard work for you, it
kind of scales your ability."
>> Yeah. And so, um, I'll make it slightly
bigger because I think it's a little
small. Um,
so now I'm also just going to ask it to
pull down a file for me. And so another
thing is it has access to resources. So
any file that you have access to on
GitHub, like in any revision of it or
branch or whatever, you can send off the
agent to just go and get a copy of it.
And so it already pulled down the index
html it asked for. And I also have the
preview plugin installed. So I can
actually just look at the this was a
silly vibe coding project I did for uh
an like a fun example website. Um
and um
uh the coding agent prompt I did earlier
to assign coding agent actually was uh
sent it off to work on different
revisions of this uh website. So, um, if
I go back into my browser and I have a
look at our agents HQ, I think I might
need to Oh, no, I don't even need to
refresh. So, we can see uh the latest
agent session that I triggered is
showing up and it actually also uses
GitHub's MCP server itself. So if you
reference issues in the repo it's
working on uh in your issue, it can then
go off and get them for example on uh
other things that it can do too. So uh
that's not going to finish I think
probably within 15 minutes. So what I
will do is just show you that um uh
previous time I told it to redesign that
web page.
Uh, let me see if I can find one that's
got a nice
a nice output. Yeah.
How's this? So, we can see the pull
request that gets generated. And, uh, I
think it should hopefully finish with a
before and after screenshot of of the
work it did. So, you can just kind of
when you think of ideas, just say them,
tell it to go off and do it, and when
you come back, you've got a pull
request. hopefully. And if you don't
like it, you can be like, um, you know,
uh, I wanted it to be even more extreme.
And then, uh, you can steer the sessions
as well. So like uh really I guess what
I'm trying to show is like once you get
addicted to using like having the MCP
and the various agentic tools that you
can connect with it, you just walk
around like I use GitHub's mobile app to
edit websites like personal websites
when I'm walking in the park and things
and uh you know by the time you're home
it's like there's a real version of it
you can hold in your hands and you could
pull it down maybe do some more coding
on it like tweak it
>> and this is actually demonstrating two
MCP servers. So the copilot coding agent
by default has the GitHub MCP server
installed but also has the Playright MCP
server installed and so this is what
drives web browsers. It's sort of a
human computer interaction agent and
that's where it's taking the
screenshots. So, this is super useful,
especially if you're not on your
machine. Like Sam said with his phone,
you tell it to do something. If you're
especially if you're building a website,
although even with CLI, it'll kind mock
it up as a website and it'll take the
screenshot and so you can then see the
result of the work without having to
locally install whatever it did, build
it and deploy it and test it like that.
It's just a really quick round trip that
you can do with the coding agent and
then give it immediate feedback.
>> And very like lastly for the live demo,
um I've just asked it to pull down a
physical image. So hopefully, oh, it's
doing the summarizing. So I'm just going
to start a new one. I think it'll be
faster. Um,
all right. So it's pulled down an image
file and then so you can use multimedia
and stuff as well. So um, it's actually
able to read the content of the image in
the agent and provide access to it
locally. So, whatever it was I wanted to
do, whether it's a design mockup or an
image I want to put in the repo, like I
can just pull stuff from anywhere on
GitHub. Um, so, uh, Toby, I think I'll
pass it back to you for closing
comments. So, I we we browse through a
lot of fun stuff you can do with the
GitHub MCP server. Um, but you can also
use it to scale. So, for instance, the
GitHub MCP server, like we said, is a
super popular open source project. It's
got over a thousand forks, which means
we get a lot of issues and pull requests
given to us like on a daily basis. So,
as a product manager, it's very helpful
for me to come in and say like summarize
the last 30 days or the last week of
issues and classify them by priority or
cluster them by topic. And so, it allows
me to sort of sort and scale this really
high volume of information that would be
quite difficult to do otherwise. So, I
think we've got a bunch of different
tool sets. So, to you can break up the
tools by use case. We've got repos,
search or whatever. um you have def
dedicated endpoints and ways to
configure the MTP server to just have
the tools that you want. I think all of
this is documented in the repos. So I'd
encourage you to kind of dig through our
our open source repo. Start star the
repo while you're there. Um and if you
look at the docs, you have a lot of
options there, including like putting it
into readonly mode. Um defining just the
tool sets you want. Uh we've got secret
scanning in there so it just the agent
doesn't push like your tokens up into a
public repo. Um we in we integrate with
the enterprise products. So if you're uh
GHC, you can use the the MCP server with
that. And like I said, it's in C-pilot
coding agent as one of the default MCP
servers.
Um and finally, you should go to our
registry. So this is something that we
just launched, and it's right now just a
list of highquality partner servers,
including the GitHub MCP server, but
we're going to be hooking into the OSS
MCP registry and allowing
self-publication. So this is going to
grow very quickly to thousands of
servers as soon as we do that. So, so
watch this space, but check out
github.com/mcp and find a bunch of other
cool MCP servers.
>> Yeah. And the last thing I wanted to
leave you with is just please,
if you can do one thing after this, if
you haven't, like load up agent mode, go
to github.com/mcp,
just install the MCP server and just
play with it. Like ask it to summarize
issues, try and vibe code, like just see
for yourself because it's awesome.
Thank you very much. Thank you.