alt.hn

3/16/2026 at 3:25:36 PM

Apideck CLI – An AI-agent interface with much lower context consumption than MCP

 https://www.apideck.com/blog/mcp-server-eating-context-window-cli-alternative

by gertjandewilde

3/16/2026 at 3:44:52 PM

I'm getting tired of everyone saying "MCP is dead, use CLIs!".

Yes, MCP eats up context windows, but agents can also be smarter about how they load the MCP context in the first place, using similar strategy to skills.

The problem with tossing it out entirely is that it leaves a lot more questions for handling security.

When using skills, there's no implicit way to be able to apply policies in the sane way across many different servers.

MCP gives us a registry such that we can enforce MCP chain policies, i.e. no doing web search after viewing financials.

Doing the same with skills is not possible in a programatic and deterministic way.

There needs to be a middle ground instead of throwing out MCP entirely.

by caust1c

3/16/2026 at 8:02:51 PM

IMO if you want a metadata registry of how actions work so you can make complicated, fragile, ACL rule systems of actions, then make that. That doesn't need to be loaded into a context window to make that work and can be expanded to general API usage, tool usage, cli usage, and so on. You can load a gh cli metadata description system and so on.

MCPs are clunky, difficult to work with and token inefficient and security orgs often have bad incentive design to mostly ignore what the business and devs need to actually do their job, leading to "endpoint management" systems that eat half the system resources and a lot of fig leaf security theatre to systematically disable whatever those systems are doing so people can do their job in an IT equivalent that feels like the TSA.

Thank god we moving away from giving security orgs these fragile tools to attach ball and chains to everyone.

by novok

3/16/2026 at 6:23:27 PM

I feel like I don't fully understand mcp. I've done research on it but I definitely couldn't explain it. I get lost on the fact that to my knowledge it's a server with API endpoints that are well defined into a json schema then sent the to LLM and the LLM parses that and decides which endpoints to hit (I'm aware some llms use smart calling now so they load the tool name and description but nothing else until it's called). How exactly are you doing the process of stopping the LLM from using web search after it hits a certain endpoint in your MCP server? Or is this referring strictly to when you own the whole workflow where you can then deny websearch capabilities on the next LLM step?

Are there any good docs youve liked to learn about it, or good open source projects you used to get familiar? I would like to learn more

by ewild

3/16/2026 at 4:02:19 PM

It is a weird trend. I see the appeal of Skills over MCP when you are just a solo dev doing your work. MCP is incredibly useful in an organization context when you need to add controls and process. Both are useful. I feel like the anti-MCP push is coming from people who don't need to work in a large org.

by yoyohello13

3/16/2026 at 5:14:46 PM

Not sure. Our big org, banned MCPs because they are unsafe, and they have no way to enforce only certain MCPs (in github copilot).

by krzyk

3/16/2026 at 5:25:15 PM

But skills where you tell the LLM to shell out to some random command are safe? I'm not sure I understand the logic.

by thenewnewguy

3/16/2026 at 6:10:06 PM

You can control an execution context in a superior manner than a rando MCP server.

MCP Security 2026: 30 CVEs in 60 Days - https://news.ycombinator.com/item?id=47356600 - March 2026

(securing this use case is a component of my work in a regulated industry and enterprise)

by toomuchtodo

3/16/2026 at 6:35:03 PM

I think big companies already protect against random commands causing damage. Work laptops are tightly controlled for both networking and software.

by newswasboring

3/16/2026 at 6:30:58 PM

Shameless plug: im working on a product that aims to solve this: https://www.gatana.ai/

by thecopy

3/16/2026 at 6:09:34 PM

Isn’t it possible to proxy LLM communication and strip out unwanted MCP tool calls from conversations? I mean if you’re going to ban MCPs, you’re probably banning any CLI tooling too, right?

by mbreese

3/16/2026 at 5:36:40 PM

We only allow custom MCP servers.

by yoyohello13

3/16/2026 at 5:17:08 PM

> I feel like the anti-MCP push is coming from people who don't need to work in a large org.

Any kind of social push like that is always understood to be something to ignore if you understand why you need to ignore it. Do you agree that a typical solo dev caught in the MCP hype should run the other way, even if it is beneficial to your unique situation?

by 9rx

3/16/2026 at 5:40:07 PM

Id agree solo devs can lean toward skills. I liken skills to a sort of bash scripts directory. And for personal stuff I generally use skills only.

by yoyohello13

3/16/2026 at 6:56:18 PM

> I'm getting tired of everyone saying "MCP is dead, use CLIs!".

The people saying this and attacking it should first agree about the question.

Are you combining a few tools in the training set into a logical unit to make a cohesive tool-suite, say for reverse engineering or network-debugging? Low stakes for errors, not much on-going development? Great, you just need a thin layer of intelligence on top of stack-overflow and blog-posts, and CLI will probably do it.

Are you trying to weld together basically an AI front-end for an existing internal library or service? Is it something complex enough that you need to scale out and have modular access to? Is it already something you need to deploy/develop/test independently? Oops, there's nothing quite like that in the training set, and you probably want some guarantees. You need a schema, obviously. You can sort of jam that into prompts and prayers, hope for the best with skills, skip validation and risk annotations being ignored, trust that future opaque model-change will be backwards compatible with how skills are even selected/dispatched. Or.. you can use MCP.

Advocating really hard for one or the other in general is just kind of naive.

by robot-wrangler

3/16/2026 at 4:22:44 PM

Skills are just prompts, so policy doesn't apply there. MCP isn't giving you any special policy control there, it's just a capability border. You could do the same thing with a service mesh or any other capability compartmentalization technique.

The only value in MCP is that it's intended "for agents" and it has traction.

by CuriouslyC

3/16/2026 at 4:27:58 PM

> Yes, MCP eats up context windows, but agents can also be smarter about how they load the MCP context in the first place, using similar strategy to skills.

I have been keeping an eye on MCP context usage with Claude Code's /context command.

When I ran it a couple months ago, supabase used 13.2k tokens all the time, with the search_docs tool using 8k! So, I disabled that tool in my config.

I just ran /context now, and when not being used it uses only ~300 tokens.

I have a question. Does anyone know a good way to benchmark actual MCP context usage in Claude Code now? I just tried a few different things and none of them worked.

by consumer451

3/16/2026 at 4:08:58 PM

Towards the end of the article, they do write about some things that MCP does better.

by skybrian

3/16/2026 at 4:17:06 PM

Tool search pretty much completely negates the MCP context window argument.

by il

3/16/2026 at 7:45:57 PM

Evidence?

by siva7

3/16/2026 at 4:06:36 PM

I agree, and it's context-dependent when to use what (the author mentions use cases for other solutions). I'm glad there are multiple solutions to choose from.

by mvrckhckr

3/16/2026 at 6:50:36 PM

This is the right framing. The chain policy problem is what happens when you ask the registry to be the entitlement layer.

Here's a longer piece on why the trust boundary has to live at the runtime level, not the interface level, and what that means for MCP's actual job: https://forestmars.substack.com/p/twilight-of-the-mcp-idols

by polynomial

3/16/2026 at 3:57:13 PM

MCPs are handy in their place. Agents calling CLI locally is much more efficient.

by j45

3/16/2026 at 4:10:18 PM

[dead]

by amzil

3/16/2026 at 6:20:54 PM

> Limit integrations → agent can only talk to a few services

The idea that people see this as one horn of a trilemma instead of just good practice is a bit strange. Who would complain that every import isn't a star-import? Bring in what you need at first, then load new things dynamically with good semantics for cascade / drill-down. Let's maybe abandon simple classics like namespacing and the unix philsophy for the kitchen-sink approach after the kitchen-sink thing is shown to work.

by robot-wrangler

3/16/2026 at 3:30:39 PM

10 years from now: "Can you believe they did anything with such a small context window?"

by hparadiz

3/16/2026 at 3:44:19 PM

More likely: "Can you believe they were actually trying to use LLMs for this?"

by this_user

3/16/2026 at 4:42:44 PM

OSes and software engs did not end up using less RAM.

by nipponese

3/16/2026 at 5:22:18 PM

Measurable responses to the environment lag, Moore's law has been slowing down (e: and demand has been speeding up, a lot).

From just a sustainability point, I really hope that the parent post's quote is true, because otherwise I've personally seen LLMs used over and over to complete the same task that it could have been used for once to generate a script, and I'd really like to be able to still afford to own my own hardware at home.

by gitonup

3/16/2026 at 7:23:26 PM

How many times have we implemented Hello World?

I'm using local models on a 6 year old AMD GPU that would have felt like a technology indistinguishable from magic 10 years ago. I ask it for crc32 in C and it gives me an answer. I ask it to play a game with me. It does. If I'm an isolated human this is like a magic talking box. But it's not magic. It doesn't use more energy than playing a video game either.

by hparadiz

3/16/2026 at 3:55:24 PM

10 years from now: "The next big thing: HENG - Human Engineers! These make mistakes, but when they do, they can just learn from it and move on and never make it again! It's like magic! Almost as smart as GPT-63.3-Fast-Xtra-Ultra-Google23-v2-Mem-Quantum"

by lionkor

3/16/2026 at 7:24:28 PM

I would love to live in a world where my coworkers learn from their mistakes

is this Human 2.0? I only have 1.0a beta in the office.

I get the joke but it really does highlight how flimsy the argument is for humans. IME humans frequently make simple errors everywhere they don’t learn from and get things right the first time very rarely. Damn. Sounds like LLMs. And those are only getting better. Humans aren’t.

by agoodusername63

3/16/2026 at 3:59:20 PM

Imagine believing humans don’t make the same mistakes. You live in a different universe than me buddy.

by cheevly

3/16/2026 at 4:37:42 PM

Sometimes we repeat mistakes. But humans are capable of occasionally learning. I've seen it!

by recursive

3/16/2026 at 5:27:53 PM

I've always wanted a better way to test programmers' debugging in an interview setting. Like, sometimes just working problems gets at it, but usually just the "can you re-read your own code and spot a mistake" sort of debugging.

Which is not nothing, and I'm not sure how LLMs do on that style; I'd expect them to be able to fake it well enough on common mistakes in common idioms, which might get you pretty far, and fall flat on novel code.

The kind of debugging that makes me feel cool is when I see or am told about a novel failure in a large program, and my mental model of the system is good enough that this immediately "unlocks" a new understanding of a corner case I hadn't previously considered. "Ah, yes, if this is happening it means that precondition must be false, and we need to change a line of code in a particular file just so." And when it happens and I get it right, there's no better feeling.

Of course, half the time it turns out I'm wrong, and I resort to some combination of printf debugging (to improve my understanding of the code) and "making random changes", where I take swing-and-a-miss after swing-and-a-miss changing things I think could be the problem and testing to see if it works.

And that last thing? I kind of feel like it's all LLMs do when you tell them the code is broken and ask then to fix it. They'll rewrite it, tell you it's fixed and ... maybe it is? It never understands the problem to fix it.

by saalweachter

3/16/2026 at 4:43:49 PM

I mean, that is not what they are writing buddy.

by creesch

3/16/2026 at 3:53:20 PM

I am kind of already at that point. For all the complaining about context windows being stuffed with MCPs, I am curious what they are up to and how many MCPs they have that this is a problem.

by MattGaiser

3/16/2026 at 3:41:06 PM

“640K ought to be enough for anybody”

by berziunas

3/16/2026 at 3:52:45 PM

I dunno why you're getting down voted. This is funny.

by hparadiz

3/16/2026 at 4:44:50 PM

"That was back when models were so slow and weighty they had to use cloud based versions. Now the same LLM power is available in my microwave"

by smrtinsert

3/16/2026 at 4:23:30 PM

One of the MCP Core Maintainers here, so take this with a boulder of salt if you're skeptical of my biases.

The debate around "MCP vs. CLI" is somewhat pointless to me personally. Use whatever gets the job done. MCP is much more than just tool calling - it also happens to provide a set of consistent rails for an agent to follow. Besides, we as developers often forget that the things we build are also consumed by non-technical folks - I have no desire to teach my parents to install random CLIs to get things done instead of plugging a URI to a hosted MCP server with a well-defined impact radius. The entire security posture of "Install this CLI with access to everything on your box" terrifies me.

The context window argument is also an agent harness challenge more than anything else - modern MCP clients do smart tool search that obviates the entire "I am sending the full list of tools back and forth" mode of operation. At this point it's just a trope that is repeated from blog post to blog post. This blog post too alludes to this and talks about the need for infrastructure to make it work, but it just isn't the case. It's a pattern that's being adopted broadly as we speak.

by dend

3/16/2026 at 6:00:32 PM

> modern MCP clients do smart tool search that obviates the entire "I am sending the full list of tools back and forth" mode of operation

How, "Dynamic Tool Discovery"? Has this been codified anywhere? I've only see somewhat hacky implementations of this idea

https://github.com/modelcontextprotocol/modelcontextprotocol...

Or are you talking about the pressure being on the client/harnesses as in,

https://platform.claude.com/docs/en/agents-and-tools/tool-us...

by o_____________o

3/16/2026 at 6:34:56 PM

More of the latter than the former. The protocol itself is constrained to a set of well-defined primitives, but clients can do a bunch of pre-processing before invoking any of them.

by dend

3/16/2026 at 6:55:08 PM

I ran into this exact problem building a MCP server. 85 tools in experimental mode, ~17k tokens just for the tool manifest before any work starts.

The fix I (well Codex actually) landed on was toolset tiers (minimal/authoring/experimental) controlled by env var, plus phase-gating, now tools are registered but ~80% are "not connected" until you call _connect. The effective listed surface stays pretty small.

Lazy loading basically, not a new concept for people here.

by bazhand

3/16/2026 at 4:10:26 PM

CLIs are great for some applications! But 'progressive disclosure' means more mistakes to be corrected and more round trips to the model - every time[1] you use the tool in a new thread. You're trading latency for lower cost/more free context. That might be great! But it might not be, and the opposite trade (more money/less context for lower latency) makes a lot of sense for some applications. esp. if the 'more money' part can be amortized over lots of users by keeping the tool definitions block cached.

[1]: one might say 'of course you can just add details about the CLI to the prompt' ... which reinvents MCP in an ad hoc underspecified non-portable mode in your prompt.

by kristjansson

3/16/2026 at 5:02:15 PM

This is a fair trade-off and the post should probably be more explicit about it. You're right that progressive disclosure trades latency for cost and context space. For some workloads that's the wrong trade.

The amortization point is interesting too. If you're running a support agent that calls the same 5 tools thousands of times a day, paying the schema cost once and caching it makes total sense. The post covers this in the "tightly scoped, high-frequency tools" section but your framing of it as a caching problem is cleaner.

On the footnote: guilty as charged, partially. The ~80 token prompt is a minimal bootstrap, not a full schema. It tells the agent how to discover, not what to call. But yeah, the moment you start expanding that prompt with specific flags and patterns, you're drifting toward a hand-rolled tool definition. The difference is where you stop. 80 tokens of "here's how to explore" is different from 10,000 tokens of "here's everything you might ever need." But the line between the two is blurrier than the post implies. Fair point.

by amzil

3/16/2026 at 4:36:27 PM

The industry is talking in circles here. All you need is "composability".

UNIX solved this with files and pipes for data, and processes for compute.

AI agents are solving this this with sub-agents for data, and "code execution" for compute.

The UNIX approach is both technically correct and elegant, and what I strongly favor too.

The agent + MCP approach is getting there. But not every harness has sub-agents, or their invocation is non-deterministic, which is where "MCP context bloat" happens.

Source: building an small business agent at https://housecat.com/.

We do have APIs wrapped in MCP. But we only give the agent BASH, an CLI wrapper for the MCPs, and the ability to write code, and works great.

"It's a UNIX system! I know this!"

by nzoschke