This is what I've been working on. I've written a project wrapper CLI that has a consistent interface that wraps a bunch of tools. The reason I wrote the CLI wrapper is for consistency. I wrote a skill that states when and how to call the CLI. AI agents are frequently inconsistent with how they will call something. There are some things I want executed in a consistent and controlled way.

It is also easier to write and debug CLI tooling, and other human devs get to benefit from the CLI tools. MCP includes agent instructions of how to use it, but the same can be done with skills or AGENTS.md (CLAUDE.md) for CLI.

that's what the MCP server is, except I don't always want a cli.

If I need to call API on top of a cli tool, i don't have to have a second wrapper, or extend my existing wrapper. You're suggesting I recreate everything MCP does, just so..it's my own?

MCP is just a way to use use wrappers other people have built, and to easily manage wrapping "tools", those could be cli tools, api calls, database query,etc..

cli tools aren't aware of the context window either, they're not keeping track of it. I might want my cli tool to output lots of useful text but maybe I don't want some of that for the LLM to save on tokens. Sure, I could create another cli tool to wrap my cli tool, now i have two cli tools to maintain. I'd prefer to do all the wrapping and pre-llm cleanup done in one consistent place. The instructions for the LLM letting it know what tools, parameters,etc.. are available is also defined in a consistent way, instead of me inventing my own scheme. I'd rather just focus on getting a usable agent.

I don't get the issue people in this thread have with MCP, is there some burden about it I haven't ran into? It's pretty easy to set one up.