Introducing the Developer Knowledge API and MCP Server(developers.googleblog.com)
developers.googleblog.com
Introducing the Developer Knowledge API and MCP Server
https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/
36 comments
You don't even need to do git or a tarball! HTTP/HTML already has an "API" for serving Markdown to any agent like a LLM which wants it, because you can easily set a server to return Markdown with an accept-encoding (kinda why that functionality exists in the first place).
I set my nginx to return the Markdown source (which is just $URL.md) for my website; any LLM which wants up-to-date docs from my website can do so as easily as `curl --header 'Accept: text/markdown' 'https://gwern.net/archiving'`. One simple flag. Boom, done.
I set my nginx to return the Markdown source (which is just $URL.md) for my website; any LLM which wants up-to-date docs from my website can do so as easily as `curl --header 'Accept: text/markdown' 'https://gwern.net/archiving'`. One simple flag. Boom, done.
The point of MCP is discoverability. A crud app is better, except you have to waste context telling your LLM a bunch of details. With MCP you only put into it's context what the circumstances are where it applies, and it can just invoke it. You could write a bunch of little wrapper scripts around each api you want to use and have basically reinvented MCP for yourself.
Most MCPs I've seen could be:
1. A cli script or small collection of scripts
2. A very short markdown file explaining how it works and when to use it.
3. Optionally, some other reference markdown files
Context use is tiny, nearly everything is loaded on demand.
And as I'm writing this, I realize it's exactly what skills are.
Can anyone give an example of something that this wouldn't work for, and which would require MCP instead?
1. A cli script or small collection of scripts
2. A very short markdown file explaining how it works and when to use it.
3. Optionally, some other reference markdown files
Context use is tiny, nearly everything is loaded on demand.
And as I'm writing this, I realize it's exactly what skills are.
Can anyone give an example of something that this wouldn't work for, and which would require MCP instead?
But this is entirely besides the point. The point of MCP is bundling those exact things into a standardized plugin that’s easy for people to share with others.
MCP is useful because I can add one in a single click for an external service (say, my CI provider). And it gives the provider some control over how the agent accesses resources (for example, more efficient/compressed, agent-oriented log retrieval vs the full log dump a human wants). And it can set up the auth token when you install it.
So yeah, the agent could write some those queries manually (might need me to point it to the docs), and I could write helpers… or I could just one-click install the plugin and be done with it.
I don’t get why people get worked up over MCP, it’s just a (perhaps temporary) tool to help us get more context into agents in a more standard way than everyone writing a million different markdown files and helper scripts.
MCP is useful because I can add one in a single click for an external service (say, my CI provider). And it gives the provider some control over how the agent accesses resources (for example, more efficient/compressed, agent-oriented log retrieval vs the full log dump a human wants). And it can set up the auth token when you install it.
So yeah, the agent could write some those queries manually (might need me to point it to the docs), and I could write helpers… or I could just one-click install the plugin and be done with it.
I don’t get why people get worked up over MCP, it’s just a (perhaps temporary) tool to help us get more context into agents in a more standard way than everyone writing a million different markdown files and helper scripts.
"The point of MCP is bundling those exact things into a standardized plugin that’s easy for people to share with others." Like... a CLI/API?
"MCP is useful because I can add one in a single click for an external service" Like... a CLI/API? [edit: sorry, not click, single 'uv' or 'brew' command]
"So yeah, the agent could write some those queries manually" Or, you could have a high-level CLI/API instead of a raw one?
"I don’t get why people get worked up over MCP" Because we tried them and got burned?
"to help us get more context into agents in a more standard way than everyone writing a million different markdown files and helper scripts." Agreed it's slightly annoying to add 'make sure to use this CLI/API for this purpose' in AGENTS.md but really not much. It's not a million markdown files tho. I think you're missing some existing pattern here.
Again, I fail to see how most MCPs are not lazy tools that could be well-scoped discoverable safe-to-use CLI/APIs.
"MCP is useful because I can add one in a single click for an external service" Like... a CLI/API? [edit: sorry, not click, single 'uv' or 'brew' command]
"So yeah, the agent could write some those queries manually" Or, you could have a high-level CLI/API instead of a raw one?
"I don’t get why people get worked up over MCP" Because we tried them and got burned?
"to help us get more context into agents in a more standard way than everyone writing a million different markdown files and helper scripts." Agreed it's slightly annoying to add 'make sure to use this CLI/API for this purpose' in AGENTS.md but really not much. It's not a million markdown files tho. I think you're missing some existing pattern here.
Again, I fail to see how most MCPs are not lazy tools that could be well-scoped discoverable safe-to-use CLI/APIs.
That's literally what they are. It's a dead simple self describing JSONRPC API that you can understand if you spend 5 seconds looking at it. I don't get why people get so worked up over it as if it's some big over-engineered spec.
I can run an MPC on my local machine and connect it to an LLM FE in a browser.
I can use the GitHub MCP without installing anything on my machine at all.
I can run agents as root in a VM and give them access to things via an MCP running outside of the VM without giving them access to secrets.
It's an objectively better solution than just giving it CLIs.
I can run an MPC on my local machine and connect it to an LLM FE in a browser.
I can use the GitHub MCP without installing anything on my machine at all.
I can run agents as root in a VM and give them access to things via an MCP running outside of the VM without giving them access to secrets.
It's an objectively better solution than just giving it CLIs.
All true except that CLI tools are composable and don't pollute your context when run via a script. The missing link for MCP would be a CLI utility to invoke it.
How does the agent know what clis/tools it has available? If there's an `mcpcli --help` that dumps the tool calls, we've just moved the problem.
The composition argument is compelling though. Instead of clis though, what if the agent could write code where the tools are made available as functions?
The composition argument is compelling though. Instead of clis though, what if the agent could write code where the tools are made available as functions?
tools.get_foo(tools.get_bar())> what if the agent could write code where the tools are made available as functions?
Exactly, that would be of great help.
> If there's an `mcpcli --help` that dumps the tool calls, we've just moved the problem.
I see I worded my comment completely wrong... My bad. Indeed MCP tool definitions should probably be in context. What I dislike about MCP is that the IO immediately goes into context for the AI Agents I've seen.
Example: Very early on when Cursor just received beta MCP support I tried a Google Maps MCP from somewhere on the net; asked Cursor "Find me boxing gyms in Amsterdam". The MCP call then dumped a HATEOAS-annotated massive JSON causing Cursor to run out of context immediately. If it had been a CLI tool instead, Cursor could have wrapped it in say a `jq` to keep the context clean(er).
Exactly, that would be of great help.
> If there's an `mcpcli --help` that dumps the tool calls, we've just moved the problem.
I see I worded my comment completely wrong... My bad. Indeed MCP tool definitions should probably be in context. What I dislike about MCP is that the IO immediately goes into context for the AI Agents I've seen.
Example: Very early on when Cursor just received beta MCP support I tried a Google Maps MCP from somewhere on the net; asked Cursor "Find me boxing gyms in Amsterdam". The MCP call then dumped a HATEOAS-annotated massive JSON causing Cursor to run out of context immediately. If it had been a CLI tool instead, Cursor could have wrapped it in say a `jq` to keep the context clean(er).
I mean what was keeping Cursor from running jq there? It's just a matter of being integrated poorly - which is largely why there was a rethink of "we just made this harder on ourselves, let's accomplish this with skills instead"
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I'm with you because we get to specify our context more precisely.
I mean, one could argue skills are sort of MCP 2.0 fixing some of the mistakes.
The big pluses for MCPs are when:
1. They live remotely and update themselves 2. You install the skill and the scripts it uses together locally, so it can be more convenient packaging
MCPs aren't really all that complicated inherently, a lot of mistakes around them happened because they came early.
The big pluses for MCPs are when:
1. They live remotely and update themselves 2. You install the skill and the scripts it uses together locally, so it can be more convenient packaging
MCPs aren't really all that complicated inherently, a lot of mistakes around them happened because they came early.
The last time I looked at MCPs closely, they appeared to pollute context and just hang there consuming context constantly. Whereas a self-documenting API or CLI tool enabled progressive discovery.
Has this changed?
My uncharitable interpretation is that MCP servers are NJ design for agents, and high quality APIs and CLIs are MIT design.
Has this changed?
My uncharitable interpretation is that MCP servers are NJ design for agents, and high quality APIs and CLIs are MIT design.
There has been some improvement in that area.
But at the end of the day, MCP is about making it easy/standard to pull in context from different sources. For example, to get logs from a CI run for my PR, or to look at jira tickets, or to interact with GitHub. Sure, a very simple API baked into the model’s existing context is even better (Claude will just use the GH CLI for lots of stuff, no MCP there.)
MCP is literally just a way for end users to be able to quickly plug in to those ecosystems. Like, yeah, I could make some extra documentation about how to use my CI provider’s API, put an access token somewhere the agent can use… or I could just add the remote MCP and the agent has what it needs to figure out what the API looks like.
It also lets the provider (say, Jira) get some control over how models access your service instead of writing whatever API requests they feel like.
Like, MCP is really not that crazy. It’s just a somewhat standard way to make plugins for getting extra context. Sure, agents are good at writing with API requests, but they’re not so good at knowing why, when, or what to use.
People get worked up over the word “protocol” like it has to mean some kind of super advanced and clever transport-layer technology, but I digress :p
But at the end of the day, MCP is about making it easy/standard to pull in context from different sources. For example, to get logs from a CI run for my PR, or to look at jira tickets, or to interact with GitHub. Sure, a very simple API baked into the model’s existing context is even better (Claude will just use the GH CLI for lots of stuff, no MCP there.)
MCP is literally just a way for end users to be able to quickly plug in to those ecosystems. Like, yeah, I could make some extra documentation about how to use my CI provider’s API, put an access token somewhere the agent can use… or I could just add the remote MCP and the agent has what it needs to figure out what the API looks like.
It also lets the provider (say, Jira) get some control over how models access your service instead of writing whatever API requests they feel like.
Like, MCP is really not that crazy. It’s just a somewhat standard way to make plugins for getting extra context. Sure, agents are good at writing with API requests, but they’re not so good at knowing why, when, or what to use.
People get worked up over the word “protocol” like it has to mean some kind of super advanced and clever transport-layer technology, but I digress :p
You're making the convenience argument, but I'm making the architecture argument. They're not the same thing.
You say "a very simple API baked into the model's existing context is even better". So we agree? MCP's design actively discourages that better path.
"Agents are good at writing API requests, but not so good at knowing why, when, or what to use". This is exactly what progressive discovery solves. A good CLI has --help. A good API has introspection. MCP's answer is "dump all the tool schemas into context and let the model figure it out," which is O(N) context cost at all times vs O(1) until you actually need something.
"It's just a standard way to make plugins" The plugin pattern of "here are 47 tool descriptions, good luck" is exactly the worse-is-better tradeoff I'm describing. Easy to wire up, expensive at runtime, and it gets worse as you add more servers.
The NJ/MIT analogy isn't about complexity, it's about where the design effort goes. MCP puts the effort into easy integration. A well-designed API puts the effort into efficient discovery. One scales, the other doesn't.
You say "a very simple API baked into the model's existing context is even better". So we agree? MCP's design actively discourages that better path.
"Agents are good at writing API requests, but not so good at knowing why, when, or what to use". This is exactly what progressive discovery solves. A good CLI has --help. A good API has introspection. MCP's answer is "dump all the tool schemas into context and let the model figure it out," which is O(N) context cost at all times vs O(1) until you actually need something.
"It's just a standard way to make plugins" The plugin pattern of "here are 47 tool descriptions, good luck" is exactly the worse-is-better tradeoff I'm describing. Easy to wire up, expensive at runtime, and it gets worse as you add more servers.
The NJ/MIT analogy isn't about complexity, it's about where the design effort goes. MCP puts the effort into easy integration. A well-designed API puts the effort into efficient discovery. One scales, the other doesn't.
I tried using the Microsoft azure devops MCP and it immediately filled up 160k of my context window with what I can only assume was listing out an absurd number of projects. Now I just instruct it to make direct API calls for the specific resources, I don’t know maybe I’m doing something wrong in Cursor, or maybe Microsoft is just cranking out garbage (possible), but to get that context down I had to uncheck all the myriad features that MCP supplies.
> Why not just a tar with all the docs? How big are they? A couple MB?
fabien@debian2080ti:~$ du -sh /usr/share/man/ #all lang
52M /usr/share/man/
MCP servers are the correct way to offer this service. Webpages are for humans, these served documents are for agents.
You could argue that they could just let the agent curl an agent-optimized API, and that is what MCP is.
You could argue that they could just let the agent curl an agent-optimized API, and that is what MCP is.
Sure, but Google isn't maintaining two sets of documentation here, the MCP server is just a thin wrapper around the webpage with a little search tool. So it's still the docs for humans just with a different delivery mechanism. Which is fine, but you can understand when hypertext exists largely for this exact purpose folks would find it odd and over complicated to reinvent the web over jsonrpc for robots.
How do you manage auth for services that use OAuth?
I’ve been wrapping the agent’s curl calls in a small cli that handles the auth but I’m wondering if other people have come up with something lighter/more portable.
I’ve been wrapping the agent’s curl calls in a small cli that handles the auth but I’m wondering if other people have come up with something lighter/more portable.
Having picked out an Oauth flow is one of the main selling points of MCP
> Why do people have to make this stuff so complicated?
Job security.
Job security.
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AWS has theirs as well: https://awslabs.github.io/mcp/servers/aws-documentation-mcp-...
As it turns out these are very helpful for obscure features and settings buried in the documentation.
As it turns out these are very helpful for obscure features and settings buried in the documentation.
So an mcp server just for google specific public docs? Aren't there a dozen of them like Context7 (https://context7.com/) that already do this?
Also curious how this differentiates itself from Context7, which has been the go-to choice for something like this. Where's the benefit?
I need to give this a try, but nowadays I am reluctant to fire up Gemini CLI due to its insane appetite for tokens.
It doesnt matter if your LLM in/out tokens are a bit cheaper than competitors when you use 3x of them on every prompt. Maybe Google should focus on addressing that first?
It doesnt matter if your LLM in/out tokens are a bit cheaper than competitors when you use 3x of them on every prompt. Maybe Google should focus on addressing that first?
I can relate to this. Gemini 3 doesn’t know a thing about iOS 26 or Liquid Glass. It constantly assumes this is some custom view that I want it to develop and ends up building something out the previous gen apis like ultrathinmaterial.
Would this be any better than just pasting links to the appropriate documentation for the technology you want to use in your AGENTS.md file? I suppose it's better if it's a single giant text file so there are fewer agent iterations navigating links within the docs but then doc sites could just provide that, like https://docs.avohq.io/3.0/llm-support.html
There’s something almost nostalgic about it: cutting-edge technology wrapped in layers of bureaucracy that feel lovingly inherited from another era.
This must be what gwern meant when he said to write for AI.
This could probably be a downloadable skill, but they will get more data about which docs coding agents are reading if it's an API call.
Why not just an http server providing access to markdown files? Your llm can curl the files.
Want it to be easy to update? Make it a git repo with all the docs. My agent already knows to always do a git fetch before interacting with a repo in a new session. Or you can fetch on a timer. Whatever.
I haven't yet figured out the point of this MCP stuff. Codex seems to have innate knowledge of how to curl jira and confluence and gitlab and prometheus and SQL databases and more. All you need to configure is a .netrc file and put the hostname in AGENTS.md. Are MCP tools even composable? Like can the model pipe the response to grep or jq or another MCP call without it entering/wasting context? Or is a normal CRUD API strictly more powerful and easier to use?