Why do people have to make this stuff so complicated? An API that requires a key and enabling an MCP server and configuring your client to fetch markdown files on the fly? There's documentation on how to set things up to be able to get the documentation? Why not just a tar with all the docs? How big are they? A couple MB? Agents are really good at using grep on text files. So is my text editor.
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?
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.
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.
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.
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.
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 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?
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
Why do people have to make this stuff so complicated? An API that requires a key and enabling an MCP server and configuring your client to fetch markdown files on the fly? There's documentation on how to set things up to be able to get the documentation? Why not just a tar with all the docs? How big are they? A couple MB? Agents are really good at using grep on text files. So is my text editor.
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?
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.
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?
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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.
2 replies →
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?
Yep... in fact there are already a lot of tooling for that, e.g. man obviously but also apropos.
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.
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.
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.
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.
Microsoft too:
https://learn.microsoft.com/training/support/mcp
https://github.com/MicrosoftDocs/mcp
https://devblogs.microsoft.com/dotnet/microsoft-learn-mcp-se...
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?
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 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.
This must be what gwern meant when he said to write for AI.
Why not just an http server providing access to markdown files? Your llm can curl the files.