Agents waste a lot of tokens on editing, sandboxes, passing info back and forth from tool calls and subagents.
Love the pragmatic mix of content based addressing + line numbers. Beautiful.
Why would I use an MCP when I can use a cli tool that the model likely trained on how to use?
And not everything has a CLI, but in any case, the comment I was replying to was suggesting building my own CLI, which presumably the LLM wasn’t trained on.
Maybe my understanding of MCP is wrong, my assumption is that it’s a combination of a set of documented tools that the LLM can call (which return structured output), and a server that actually receives and processes those tool calls. Is that not right? What’s the downside?
And the MCP already only has the most essential tools for my workflow: the ability to run queries against a few databases.
With CC you can do a /cost to see how much your session cost in dollar terms, that's a good benchmark IMO for plugins, .md files for agents, and so on. Minimize the LLM cost in the way you'd minimize typical resource usage on a computer like cpu, ram, storage etc.