It's just a way to provide a "library of methods" / API that the LLM models can "call", so basically giving them method names, their parameters, the type of the output, and what they are for,

and then the LLM model will ask the MCP server to call the functions, check the result, call the next function if needed, etc

Right now if you go to ChatGPT you can't really tell it "open Google maps with my account, search for bike shops near NYC, and grab their phone numbers", because all he can do is reply in text or make images

with a "browser MCP" it is now possible: ChatGPT has a way to tell your browser "open Google maps", "show me a screenshot", "click at that position", etc

Isn't the idea of AI agent talking to each by telling LLM model to reply say in, JSON and with some parameter value map to, say function in Python code? That in retrospect, given context {prompt} to LLM will be able to call said function code?

Is this what 'calling' is?

Yes exactly. MCP just formalize this a bit better

> with a "browser MCP" it is now possible: ChatGPT has a way to tell your browser "open Google maps", "show me a screenshot", "click at that position", etc

It seems strange to me to focus on this sort of standard well in advance of models being reliable enough to, ya know, actually be able perform these operations on behalf of the user with any sort of strong reliability that you would need for widespread adoption to be successful.

Cryptocurrency "if you build it they'll come" vibes.

I think MCPs compensate for the unreliability issue by providing a minimal and well defined interface to a controlled set of actions. That way, the llm doesn't have to be as reliable thinking what it needs to do and in acting, just in choosing what to do from a short list.

You can provide an MCP for Pokemon Red, but Claude will still flounder for weeks, making absurd mistakes on a game literally designed for children.

Believe me. It's not there yet.

Is there an MCP for pokemon red?

Not that im aware of, but that actually would be an interesting project.

I was referring more broadly to ClaudePlaysPokemon, a twitch stream where claude is given tool calling into a Gameboy Color emulator in order to try to play Pokemon. It has slowly made progress and i recommend looking at the stream to see just how flawed LLM's are currently for even the shortest of timelines w.r.t. planning.

I compared the two because the tool calling API here is a similar enough to an MCP configuration with the same hooks/tools (happy to be corrected on that though)

The speed that every major LLM foundational model provider has jumped on this bandwagon feels VERY artificial and astro turfy...

Maybe because the LLM improvements haven't been that good in the last year, they needed some new thing to hype it/market it.

EDIT: Don't get me wrong, the benchmark scores are indeed higher, but in my personal experience, LLMs make as many mistakes as they did before, still too unreliable to use for cases where you actually need a factually correct answer.

This is in my opinion exactly what it is. A bunch of people throwing stuff at the wall trying to show "impact."

You actually can, its called Operator and its a complete waste of time, just like 99% of agents/MCPs.

Operator is basically MCP...

And the worst part is that it opens a pandora's box of potential exploits; https://elenacross7.medium.com/%EF%B8%8F-the-s-in-mcp-stands...

That's not fault of MCP though, that's the fault of vendors peddling their MCPs while clinging to the SaaS model.

Yes, MCP is a way to streamline giving LLMs ability to run arbitrary code on your machine, however indirectly. It's meant to be used on "your side of the airlock", where you trust the things that run. Obviously it's too powerful for it to be used with third-party tools you neither trust nor control; it's not that different than downloading random binaries from the Internet.

I suppose it's good to spell out the risks, but it doesn't make sense blaming MCP itself, because those risks are fundamental aspects of the features it provides.

It's not blame, but it's a striking reality that needs to be kept at the forefront.

It introduces a substantial set of novel failure modes, like cross-tool shadowing, which aren't obvious to most folks. Making use of any externally developed tooling — even open source tools on internal architecture — requires more careful consideration and analysis than most would expect. Despite the warnings, there will certainly be major breaches on these lines.

Most of these are not a real concern with remote servers with Oauth. If you install the PayPal MCP MCP server from im-deffo-not-hacking-you.com than https://mcp.paypal.com/sse its the same sec model as anything else online...

The article also reeks of LLM ironically

it still is. if user has 1 bad tool, it's done!

https://invariantlabs.ai/blog/mcp-security-notification-tool...

Its the same security model as NPM/left pad yep, but consumers still use electron apps? It's a novel attack method, but its not a novel attack surface

At the risk of it sounding like i support theft; the automobile, you know, enabled the likes of Bonnie and Clyde and that whole era of lawlessness. Until the fbi and crossing county lines became a thing.

So im not sure id give up the sum total progress of the automobile just because the first decade was a bad one

MCP is a standard to plug useful tools into AI models so they can use them. The concept looks confusingly reversed and non-obvious to a normal person, although devs don't see this because it looks like their tooling.

I know what you mean, I think MCP is being widely adopted but it's not grassroots.. its a quick entry to this market by an established AI company trying to dominate the mind/market share of developers before consensus can be reached developers.