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I still prefer MCP over skills

david.coffee

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Re: I still prefer MCP over skills

#81
post #71
post #39

Earlier quoted context omitted.

MCP is an API with strictly defined inputs and outputs.

Does MCP support authentication, SSO?

It supports OAuth, IIRC. But I suppose the internal chatbot itself would require auth, and pass that down to the tools it calls.

Re: I still prefer MCP over skills

#82
post #39

Earlier quoted context omitted.

MCP is an API with strictly defined inputs and outputs.

This is obviously not what it is. If I give you APIGW would you be able to implement an MCP server with full functionality without a large amount of middleware?

Sorry, could you rephrase that?

Re: I still prefer MCP over skills

#83
CLI is massively superior to MCP in my experience. First, because I also understand what's going on and do it myself if necessary. Second because it's so much cheaper in terms of tokens it's not even funny

Re: I still prefer MCP over skills

#86
> The core philosophy of MCP is simple: it’s an API abstraction. The LLM doesn’t need to understand the how; it just needs to know the what.

Wrong. It needs to "understand" both these things. The only difference is where and how the strings explaining them are generated.

Re: I still prefer MCP over skills

#87

The "only skills" people are usually non-technical and the "only CLI" people are often solo builders. MCP makes a lot of sense for enterprise IMO. Defines auth and interfaces in a way that's a natural extension of APIs.

I think many of us have been burned by the absolutely awful and unstable JIRA MCP and found that skills using `acli` actually work and view the rest of the MCP space thru that lens. Lots of early - and current! - MCP implementations were bad. So it’s an uphill battle to rebuild reputation.

Can you share more about acli?

Literally my biggest use case for MCP is Jira and Confuence

Re: I still prefer MCP over skills

#88
post #10

I could not agree any less with the author. I don’t want APIs, I want agents to use the same CLI tooling I already use that is locally available. If my agents are using CLI tooling anyways there is no need to add an extra layer via MCP. I don’t want remote MCP calls, I don’t even want remote models but that’s cost prohibitive. If I need to call an API, a skill with existing CLI tooling is more than capable.

I keep getting hung up on securely storing and using secrets with CLI vs MCP. With MCP, you can run the server before you run the agent, so the agent never even has the keys in its environment. That way. If the agent decides to install the wrong npm package that auto dumps every secret it can find, you are less likely to have it sitting around. I haven’t figured out a good way to guarantee that with CLIs.

And in a skill, I can store the secret in the skill itself, or a secure storage the skill accesses, and the agent never gets to see the secret.

Sure, if I want my agents to use naked curl on the CLI, they need to know secrets. But that's not how I build my tools.

Re: I still prefer MCP over skills

#89
Yesterday I accidentally stumbled on a place where I could really appreciate MCP's.

I wanted to connect my Claude account to my Notion account. Apparently all you need to do is just submit the notion MCP and log in. That's it! And I was able to interact with my Notion data from my Claude account!

Imagine how hard this would be with skills? It is literally impossible because with skills, you may need to install some local CLI which Claude honestly should not allow.

If not CLI, you need to interact with their API which again can't happen because you can't authenticate easily.

MCP's fill this narrow gap in my opinion - where you don't own the runtime and you want to connect to other tools like plugins.

Re: I still prefer MCP over skills

#90
> Context Bloat: Using a skill often requires loading the entire SKILL.md into the LLM’s context window, rather than just exposing the single tool signature it needs. It’s like forcing someone to read the entire car’s owner’s manual when all they want to do is call car.turn_on().

MCP has severe context bloat just by starting a thread. If harnesses were smart enough to, during install time, summarize the tools provided by a MCP server (rather than dumping the whole thing in context), it would be better. But a worse problem is that the output of MCP goes straight into the context of the agent, rather than being piped somewhere else

A solution is to have the agent run a cli tool to access mcp services. That way the agent can filter the output with jq, store it in a file for analysis later, etc

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