191–200 of 383 posts
MCPs are overhyped and have limited value in my opinion. About 95% of the MCP servers out there are useless and can be replaced with a simple tool call.
I do think the big story here is how hyperfocused and path-dependent people got on MCP, when the actually-interesting thing is simply "tool calls". Tool calls are incredibly interesting and useful. MCP is just one means to that end, and not one of the better ones.
MCP servers are basically a tool call registries, how could it be worse than a regular tool call?
I do think the big story here is how hyperfocused and path-dependent people got on MCP, when the actually-interesting thing is simply "tool calls". Tool calls are incredibly interesting and useful. MCP is just one means to that end, and not one of the better ones.
To clarify, MCP was also a Anthropic innovation.
MCPs are overhyped and have limited value in my opinion. About 95% of the MCP servers out there are useless and can be replaced with a simple tool call.
This is a very obvious statement, but good MCP servers can be really good, and bad MCP servers can actively make things significantly worse. The problem is that most MCP servers are in the latter category. As is often the case, every product team is told that MCP is the hot new thing and they have to create an MCP server for their customers. And I've seen that customers do indeed ask for these things, because they al…
Agentic LLMs are, in a way, an attempt to commoditize entire service classes, across the board, all at once.
Personally, I welcome it. I keep saying that a lot of successful SaaS products would be much more useful and ergonomic for end users if, instead of webshit SPA, they were distributed as Excel sheets. To that I will now add: there's a lot more web services that I'd prefer be tool calls for LLMs.
Search engines have already been turned into features (why ask Google when o3 can ask it for me), but that's just an obvious case. E-mails, e-commerce, shopping, coding, creating digital art, planning, managing projects and organizations, analyzing data and trends - all those are in-scope too; everything I can imagine asking someone else to do for me is meant to eventually become a set of tool calls.
Or in short: I don't want AI in your product - I want AI of my choice to use your product for me, so I don't have to deal with your bullshit.
> imagine a folder full of skills that covers tasks like the following: > Where to get US census data from and how to understand its structure Reminds me of my first time using Wolfram Alpha and got blown away by its ability to use actual structured tools to solve the problem, compared to normal search engine. In fact, I tried again just now and am still amazed: https://www.wolframalpha.com/input?i=what%27s+the+total…
tbh wolfram alpha was the craziest thing ever. haven't done much research on how this was implemented back in the day but to achieve what they did for such complex mathematical problems without AI was kind of nuts
I've been able to build the equivalent of skills with a few markdown files. I need to remind my agent every so often to use a skill but usually once per session at most. I don't get what's so special about Claude doing this?
Part of it is that they gave a name to a useful pattern that people had already been discovering independently. Names are important, because they mean we can start having higher quality conversations about the pattern. Anthropic also realized that this pattern solves one of the persistent problems with coding agents: context pollution. You need to stuff as little material as possible into the context to enable the to…
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Part of it is that they gave a name to a useful pattern that people had already been discovering independently. Names are important, because they mean we can start having higher quality conversations about the pattern. Anthropic also realized that this pattern solves one of the persistent problems with coding agents: context pollution. You need to stuff as little material as possible into the context to enable the to…
I think you're overly enthusiastic about what's going on here (which is surprising because you've seen the trend in AI seems to be re-inventing the wheel every other year...)
MCP was conceptually quite complicated, and a pretty big lift in terms of implementation for both servers and clients.
Skills are conceptially trivial, and implementing them is easy... provided you have a full Linux-style sandbox environment up and running already. That's a big dependency but it's also an astonishingly powerful way to use LLMs based on my past 6 months of exploration.
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MCP servers are basically a tool call registries, how could it be worse than a regular tool call?
an MCP server can run code outside of the domain of tools that it supports, tool call can't
Same stuff, different name - only thing that's changed is that Anthropic got people to agree on RPC protocol.
It's not like it's a new idea, either. MCP isn't much different from SOAP or DCOM - but it works where the older approaches didn't, because LLMs are able to understand API definitions and natural-language documentation, and then map between those APIs (and user input) on the fly.
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This is true, but the reason the economics have inverted is that we can pay these new "people" <$20 for the human equivalent of ~300 hours worth of non-stop typing.
That is not true at all. The economics you’re seeing right now are akin to Uber handing out $5 airport pickups to kill the taxi industry. And even then the models are nowhere as cheap as <$20 for ~300 hours of human work.
I just took GPT-5, output is $10 per million tokens. Let's double the cost to account for input tokens which are ($1.25 per million / $0.125 if cached).
For 1 million tokens it would take a 40 wpm typist.. around 20K minutes to output that $20 of worth of text. That is just typing. So about 300 hours of non-stop effort for that $20.
So even if you say.. oh.. the real price is $100 not $20. The value changes are still shattering to the previous economic dynamics.
Then layer in that also as part of that value, the "typist" is also more skilled than the average working person in linguistics, software engineering, etc. Then that value is further magnified.
This is why I say we have only begun to barely see the disruption this will cause. Even if the models don't get better or cheaper, the potential impact is hard to grasp.
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I think you're overly enthusiastic about what's going on here (which is surprising because you've seen the trend in AI seems to be re-inventing the wheel every other year...)
I'm more excited about this than I was about MCP. MCP was conceptually quite complicated, and a pretty big lift in terms of implementation for both servers and clients. Skills are conceptially trivial , and implementing them is easy... provided you have a full Linux-style sandbox environment up and running already. That's a big dependency but it's also an astonishingly powerful way to use LLMs based on my past 6 mont…