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MCP is dead; long live MCP

chrlschn.dev

81–90 of 231 posts

Re: MCP is dead; long live MCP

#81
post #75

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 some…

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…

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.

Re: MCP is dead; long live MCP

#82
The problem with MCP isn't MCP. It's the way it's invoked by your agent.

IMO, by default MCP tools should run in forked context. Only a compacted version of the tool response should be returned to the main context. This costs tokens yes, but doesn't blow out your entire context.

If other information is required post-hoc, the full response can be explored on disk.

Re: MCP is dead; long live MCP

#83

Earlier quoted context omitted.

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.

C 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…

All MCP adds is a session token. How is that not already a solved problem?

Re: MCP is dead; long live MCP

#84

Earlier quoted context omitted.

> 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?

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.

Re: MCP is dead; long live MCP

#85
I don't know. Skill+http endpoint feel way safer, powerful and robust. The problem is usually that the entity offering the endpoint, if the endpoint is ai powered, concur in LLM costs. While via mcp the coding agent is eating that cost, unless you are also the one running the API and so can use the coding plan endpoint to do the ai thing

Re: MCP is dead; long live MCP

#86
post #85

I don't know. Skill+http endpoint feel way safer, powerful and robust. The problem is usually that the entity offering the endpoint, if the endpoint is ai powered, concur in LLM costs. While via mcp the coding agent is eating that cost, unless you are also the one running the API and so can use the coding plan endpoint to do the ai thing

If I didn't misunderstood you, it doesn't really matter if it's an endpoint or a (remote) mcp, either someone else wants to run llms to provide a service for you or they don't.

A local mcp doesn't come in play because they just couldn't offer the same features in this case.

Re: MCP is dead; long live MCP

#87
post #85

I don't know. Skill+http endpoint feel way safer, powerful and robust. The problem is usually that the entity offering the endpoint, if the endpoint is ai powered, concur in LLM costs. While via mcp the coding agent is eating that cost, unless you are also the one running the API and so can use the coding plan endpoint to do the ai thing

If I didn't misunderstood you, it doesn't really matter if it's an endpoint or a (remote) mcp, either someone else wants to run llms to provide a service for you or they don't. A local mcp doesn't come in play because they just couldn't offer the same features in this case.

The MCP server usually provides some functions you can run, possibly with some database interaction.

So when you run it, your codign agent is using AI to run that code (what to call, what parameters to pass, and so on). Via MCP, they don't pay any LLM cost; they just offer the code and the endpoint.

But this is usually messy for the coding agent since it fills up the context. While if you use skill + API, it's easier for the agent since there's no code in the context, just how to call the API and what to pass.

With something like this, you can then have very complex things happening in the endpoint without the agent worrying about context rot or being able to deal with that functionality.

But to have that difficult functionality, you also need to call an LLM inside the endpoint, which is problematic if the person offering the MCP service does not want to cover LLM costs.

So it does matter if it's an endpoint or an MCP because the agent is able to do more complex and robust stuff if it uses skill and HTTP.

Re: MCP is dead; long live MCP

#88
post #75

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 some…

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…

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.”

Re: MCP is dead; long live MCP

#89

Earlier quoted context omitted.

All the code I work on now has an MCP interface so that the LLM can debug more easily. I'd argue it is as important as the UI these days. The amount of time it has saved me is unreal. It might be worth investing a very small amount of your time in it to see if it is a good fit. Even a poor protocol can provide useful functionality.

I've just been discovering this pattern too. It's made a huge difference. Trying to get Claude to remote control an app for testing via the various other means was miserable and unreliable. I got it to build an MCP server into the app that supported sending commands to allow Claude to interact with it as if it was a user, including keypresses and grabbing screenshots, and the difference was immediate and really benef…

How does it compare to my goto: a test suite that uses Playwright?

> Claude imolement plan.md until all unit and browser tests pass

Re: MCP is dead; long live MCP

#90
I find that skills work very well. The main SKILL file has an overview of all the capabilities of my platform at a high level and each section links to a more specific file which contains the full information with all possible parameters for that particular capability.

Then I have a troubleshooting file (also linked from the main SKILL file) which basically lists out all the 'gotchas' that are unique to my platform and thus the LLM may struggle with in complex scenarios.

After a lot of testing, I identified just 5 gotchas and wrote a short section for each one. The title of each section describes the issue and lists out possible causes with a brief explanation of the underlying mechanism and an example solution.

Adding the troubleshooting file was a game changer.

If it runs into a tricky issue, it checks that troubleshooting file. It's highly effective. It made the whole experience seamless and foolproof.

My platform was designed to reduce applications down to HTML tags which stream data to each other so the goal is low token count and no-debugging.

I basically replaced debugging with troubleshooting; the 5 cases I mentioned are literally all that was left. It seems to be able to quickly assemble any app without bugs now.

The 'gotchas' are not exactly bugs but more like "Why doesn't this value update in realtime?" kind of issues. They involve performance/scalability optimizations that the LLM needs to be aware of.

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