Comment by 0xbadcafebee
9 days ago
MCP is a fixed specification/protocol for AI app communication (built on top of an HTTP CRUD app). This is absolutely the right way to go for anything that wants to interoperate with an AI app.
For a long time now, SWEs seem to have bamboozled into thinkg the only way you can connect different applications together are "integrations" (tightly coupling your app into the bespoke API of another app). I'm very happy somebody finally remembered what protocols are for: reusable communications abstractions that are application-agnostic.
The point of MCP is to be a common communications language, in the same way HTTP is, FTP is, SMTP, IMAP, etc. This is absolutely necessary since you can (and will) use AI for a million different things, but AI has specific kinds of things it might want to communicate with specific considerations. If you haven't yet, read the spec: https://modelcontextprotocol.io/specification/2025-11-25
Why is this the right way to go? It's not solving the problem it looks like it's solving. If your challenge is that you need to communicate with a foreign API, the obvious solution to that is a progressively discoverable CLI or API specification --- the normal tool developers use.
The reason we have MCP is because early agent designs couldn't run arbitrary CLIs. Once you can run commands, MCP becomes silly.
There is a clear problem that you'd like an "automatic" solution for, but it's not "we don't have a standard protocol that captures every possible API shape", it's "we need a good way to simulate what a CLI does for agents that can't run bash".
I am creator of HasMCP (my response could have a little bias). Not everyone has home/work computer by preference mostly. I know a lot of people just use iPad or Android tablet in addition to their phone. They still use applications to work on the things. This number is not a small amount of people. They need to access openworld data or service specific data. This is where MCP is still the one of the best ways.
It tries to standardize the auth, messaging, feedback loop where API can't do alone. A CLI app can do for sure but we are talking about a standard maybe the way is something like mcpcli that you can install your phone but still would you really prefer installing bunch of application to your personal device?
Some points that MCP is still not good as of today:
- It does not have a standard to manage context in a good way. You have to find your hack. The mostly accepted one search, add/rm tool. Another one is cataloging the tools.
- lack of client tooling to support elicitation on many clients (it really hurts productivity but this is not solved with cli too)
- lack of mcp-ui adoption (mcp-ui vs openai mcp app)
I would suggest keep building to help you and your users. I am not sponsor of MCP, just sharing my personal opinion. I am also creator HasCLI but kindly biased for MCP then CLI in terms of coverage and standardization.
> It tries to standardize the auth, messaging, feedback loop where API can't do alone.
If it tried to do that, you wouldn't have the pain point list.
It's a vibe coded protocol that keeps using one-directional protocols for bi-directional communication, invents its own terms for existing stuff (elicitation lol), didn't even have any auth at the beginnig etc.
It's a slow sad way of calling APIs with JSON-RPC
The biggest disappointment I have with MCP today is that many clients are still half-assed on supporting the functions outside of MCP tools.
Namely, two very useful features resources and prompts have varying levels of support across clients (Codex being one of the worst).
These two are possibly the most powerful ones since they allow consistent, org-level remote delivery of context and I would like to see all major clients support these two and eventually catch up on the other features like elicitation, progress, tasks, etc.
A lot of the reasons to use MCP are contained in the architecture document (https://modelcontextprotocol.io/specification/2025-11-25/arc...) and others. Among them, chief is security, but then there's standardization of AI-specific features, and all the features you need in a distributed system with asynchronous tasks and parallel operation. There is a lot of stuff that has nothing to do with calling tools.
For any sufficiently complex set of AI tasks, you will eventually need to invent MCP. The article posted here talks about those cases and reasons. However, there are cases when you should not use MCP, and the article points those out too.
> Among them, chief is security
The security is so chief that they had no security at all until several versions later when they hastily bolted on OAuth.
MCP is a vibe-codef protocol that rode one of the many AI hype waves where all "design documents" are post-hoc justifications.
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If the chief reason to use MCP is security, I'm sold: it's a dead letter, and we're not going to be using it a couple years from now.
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>Among them, chief is security
Considering many popular MCPs have done auth incorrectly, this made me lol
For the Agent to use CLI, don't we have to install CLI in the run-time environment first? Instead for the MCP over streamable HTTP we don't have to install anything and just specify the tool call in the context in't it?
This rolls up to my original point. I get that if you stipulate the agent can't run code, you need some kind of systems solution to the problem of "let the agent talk to an API". I just don't get why that's a network protocol coupling the agent to the API and attempting to capture the shape of every possible API. That seems... dumb.
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CLI doesn’t work for your coworkers that aren’t technical.
Have you tried to use a random API before? It’s a process of trial and error.
With the MCP tools I use, it works the first time and every time. There is no “figuring out.”
>CLI doesn’t work for your coworkers that aren’t technical.
This actually isn't true. I've written bespoke CLI tools for my small business and non-technical people run them without issue. They get intimidated at first but within a day or so they're completely used to it - it's basically just magic incantations on a black box.
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MCP also doesn't work for coworkers that are technical. It works for their agents only.
CLI works for both agents and technical people. REST API works for both agents and technical people. MCP works only for agents (unless I can curl to it, there are some HTTP based ones)
This should be trivial if you have proper API documentation in something like swagger. You can generate a cli tool with no "figuring out" anything either.
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If you can't write a good CLI I doubt you could write a good MCP
It's significantly more difficult to secure random clis than those apis. All llm tools today bypass their ignore files by running commands their harness can't control.
I'm fuzzy when we're talking about what makes an LLM work best because I'm not really an expert. But, on this question of securing/constraining CLIs and APIs? No. It is not easier to secure an MCP than it is a CLI. Constraining a CLI is a very old problem, one security teams have been solving for at least 2 decades. Securing MCPs is an open problem. I'll take the CLI every time.
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Just use a custom PATH and run in a chroot jail.
CLI sandboxing is a solved problem compared to whatever MCP is.
I don't think so. There is no MCP standard for authentication, our infosec banned MCP because of that.
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> Why is this the right way to go? It's not solving the problem it looks like it's solving. If your challenge is that you need to communicate with a foreign API, the obvious solution to that is a progressively discoverable CLI or API specification --- the normal tool developers use.
That sounds like a hack to get around the lack of MCP. If your goal is to expose your tools through an interface that a coding agent can easily parse and use, what compels you to believe throwing amorphous structured text is a better fit than exposing it through a protocol specially designed to provide context to a model?
> The reason we have MCP is because early agent designs couldn't run arbitrary CLIs. Once you can run commands, MCP becomes silly.
I think you got it backwards. Early agents couldn't handle, and the problem was solved with the introduction of an interface that models can easily handle. It became a solved problem. Now you only argue that if today's models work hard enough, they can be willed into doing something with tools without requiring a MCP. That's neat, but a silly way to reinvent the wheel - poorly.
Yes, this has been the gradual evolution of AI context and tooling. Same thing is occurring with some of the use cases of a vector DB and RAG. Once you can have the agent interact with the already existing conventional data store using existing queries, there is no point in introducing that work flow for inference.
This limits AI usage to desktops, and mostly technical oriented tasks. MCP let's you connect to your email, shop, etc, from phone chat apps.
I want CLIs for those too so I,a human, can use them
no, it's all about auth. MCP lets less-technical people plug their existing tools into agents. They can click through the auth flow in about 10 seconds and everything just works. They cannot run CLIs because they're not running anything locally, they're just using some web app. The creator of the app just needed to support MCP and they got connectivity with just about everything else that supports MCP.
Write better CLIs for the agents of the less-technical people. The MCPs you're talking about don't exist yet either. This doesn't seem complicated; MCP seems like a real dead end.
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If AI is AI, why does it need a protocol to figure out how to interact with HTTP, FTP, etc.? MCP is a way to quickly get those integrations up and running, but purely because the underlying technology has not lived up to its hyped abilities so far. That's why people think of MCP as a band-aid fix.
Why the desire to reinvent the wheel every time? Agents can do it accurately, but you have to wait for them to figure it out every time, and waste tokens on non-differentiated work
The agents are writing the mcps, so they can figure out those http and ftp calls. MCP makes it so they dont have to every time they want to do something.
I wouldnt hire a new person to read a manual and then make a bespoke json to call an http server, every single time i want to make a call, and thats not a knock on the person's intelligence. Its just a waste of time doing the same work over and over again. I want the results of calling the API, not to spend all my time figuring out how to call the API
It’s simply about making standard, centralized plugins available. Right now Claude benefits from a “link GitHub Connector” button with a clear manifest of actions.
Obviously if the self-modifying, Clawd-native development thing catches on, any old API will work. (Preferably documented but that’s not a hard requirement.)
For now though, Anthropic doesn’t host a clawd for you, so there isn’t yet a good way for it to persist customs integrations.
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each ai need context management per conversation this is something that would be very clunky to replicate on top of http or ftp (as in requiring side channel information due session and conversation management)
Everyone looks at api and sure mcp seem redundant there but look at agent driving a browser the get dom method depends on all the action performed from when the window opened and it needs to be per agent per conversation
Can you do that as rest sure sneak a session and conversation in a parameter or cookie but then the protocol is not really just http is it it's all this clunky coupling that comes with a side of unknowns like when is a conversation finished did the client terminate or were just between messages and as you go and solve these for the hundredth time you'd start itching for standardization
All MCP adds is a session token. How is that not already a solved problem?
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Because protocols provide structure that increases correctness.
It is not a guarantee (as we see with structured output schemas), but it significantly increases compliance.
You're interacting with an LLM, so correctness is already out the window. So model-makers train LLMs to work better with MCP to increase correctness. So the only reason correctness is increased with MCP is because LLMs are specifically trained against it.
So why MCP? Are there other protocols that will provide more correctness when trained? Have we tried? Maybe a protocol that offers more compression of commands will overall take up more context, thus offering better correctness.
MCP seems arbitrary as a protocol, because it kinda is. It doesn't >>cause<< the increase in correctness in of itself, the fact that it >>is<< a protocol is the reason it may increase correctness. Thus, any other protocol would do the same thing.
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If AI is AI why does it need me to prompt it?
You mean, why not ask the AI to "find a way to use FTP", including either using a tool, or writing its own code? Besides the security issues?
One simple reason is "determinism". If you ask the AI to "just figure it out", it will do that in different ways and you won't have a reliable experience. The protocol provides AI a way to do this without guessing or working in different ways, because the server does all the work, deterministically.
But the second reason is, all the other reasons. There is a lot in the specification, that the AI literally cannot figure out, because it would require custom integration with every application and system. MCP is also a client/server distributed system, which "calling a tool" is not, so it does stuff that is impossible to do on your existing system, without setting up a whole other system... a system like MCP. And all this applies to both the clients, and the servers.
Here's another way to think of it. The AI is a psychopath in prison. You want the psycho to pick up your laundry. Do you hand the psycho the keys to your car? Or do you hand him a phone, where he can call someone who is in charge of your car? Now the psycho doesn't need to know how to drive a car, and he can't drive it off a bridge. All he can do is talk to your driver and tell him where to go. And your driver will definitely not drive off a bridge or stab anyone. And this works for planes, trains, boats, etc, just by adding a phone in between.
> If AI is AI
That "AI" got renamed to "AGI"
> This is absolutely necessary since you can (and will) use AI for a million different things
the point is, is it necessary to create a new protocol?
Exactly this. I've made some MCP servers and attached tons of other people's MCP servers to my llms and I still don't understand why we can't just use OpenAPI.
Why did we have to invent an entire new transport protocol for this, when the only stated purpose is documentation?
It’s not a new protocol.
It’s JSON-RPC plus OAuth.
(Plus a couple bits around managing a local server lifecycle.)
World would be surely a saner place if instead of “MCP vs CLI” people would talk about “JSON-RPC vs execlp(3)”.
Not accurate, but at least makes on think of the underlying semantics. Because, really, what matters is some DSL to discover and describe action invocations.
By and large, it is a very simple protocol and if you build something with it, you will see that it is just a series of defined flows and message patterns. When running over streamable HTTP, it is more or less just a simple REST API over HTTP with JSON RPC payload format and known schema.
Even the auth is just OAuth.
MCP is literally "define a bespoke API using this vibe-coded protocol over JSON-RPC".
There's nothing more standard or reusable or application-agnostic about it than using an API over any of the existing protocols.
No, this misunderstands what MCP is for and how it works.
Let's say you use Claude's chat interface. How can you make Claude connect to, say, the lights in your house?
Without MCP, you would need Anthropic the company to add support to Claude the web interface to connect over a network to your home, use some custom routing software (that you don't have) to communicate over whatever lightbulb-specific IoT protocol your bulbs use, to be able to control them. Claude needs to support your specific lightbulb stack, and some kind of routing software would need to be added in your home to connect the external network to the internal devices.
But with MCP, Claude only has to support MCP. They don't have to know anything about your lightbulbs or have some custom routing thing for your home. You just need to run an MCP server that talks to the lightbulbs... which the lightbulb company should make and publish, so you don't have to do anything but download the lightbulb MCP server and run it. Now Claude can talk to your lightbulbs, and neither you nor Claude had to do any extra work.
In addition to the communication, there is also asynchronous task control features, AI-specific features, security features, etc that are all necessary for AI work. All this is baked into MCP.
This is the power of standardized communications abstractions. It's why everyone uses HTTP and doesn't have their own custom application-specific tcp-server-language. The world wide web would just be 10 websites.
No, that's not MCP. That's a pleasant idea that MCP has been shoehorned into trying to solve. But MCP the spec is far more complicated than it needs to be to support that story. Streamable HTTP transport makes it much more workable, and I imagine was designed by real people rather than the version prior to that, but it's still much more than it needs.
Ultimately, 90% of use cases would be solved by a dramatically simpler spec which was simply an API discovery mechanism, maybe an OpenAPI spec at a .well-known location, and a simple public-client based OAuth approach for authentication and authorization. The full-on DCR approach and stateful connections specified in the spec is dramatically harder to implement.
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> But with MCP, Claude only has to support MCP. They don't have to know anything about your lightbulbs
Except the fact that it has to "know" about that specific manufacturer's bespoke API aka "tool calls" for that specific lightbulb. If the manufacturer provides an API for the lightbulb.
MCP is a vibe-coded communications protocol. There's nothing more standard or re-usable in MCP than HTTP, or any protocols built over that. Hell, using GraphQL would be a more standardized, re-usable and discoverable way of doing things than MCP. Fielding ddescribed and architecture for machine-discoverable APIs in 2000
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I mean, CLI tool is also “reusable communication abstraction”, innit?
Tell me how many ways that print help message for a command you have seen and say "reusable" again. Mcp is exactly exists to solve this. The rest is just json rpc with simple key value pairs.
You can probably let llm guess the help flag and try to parse help message. But the success rate is totally depends on model you are using.
Most CLIs use `--help`, any other are just plain hostile to the users.
`-h` is also popular, but there is also possible issue of that shorthand, hence `--help`.
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