GoKawiilWhy MCP Was Always a Bad Idea
Recently I went to an all-day event centered around the latest and greatest in the MCP world. While all of the presenters were awesome and seemed to be passionate about the work they were doing, I’m honestly tired of MCP. It’s a horrible protocol built for a time when LLMs weren’t that smart, and we’ve outgrown it.
A Brief History
MCP was released in November 2024 by the Anthropic team as a protocol designed to help agents connect to external services and data sources.1 The models of the time were still relatively primitive, at least compared to what we have right now. We didn’t even have Claude Code back then, and general-purpose agentic workflows were far less reliable.
Users started to see the usefulness of giving their AI models access to external services. It enabled a level of productivity that we hadn’t seen before. We saw an explosion in MCP adoption, coinciding with a similar, if not more explosive, growth in LLM adoption across the economy.
Over time, MCP continued to evolve under Anthropic’s stewardship before it was eventually donated to the Agentic AI Foundation, under the Linux Foundation, in 2025.2
The MCP Industrial Complex
With the huge growth in adoption, users started to add many MCP servers to their setups, and they started running into the context bloat issue. Each server would come with multiple tools, each with its own schema, which started to overload the context of all of these models. Harness developers found many tricks around this, including generic search/execute patterns now offered by platforms like Composio, MintMCP, and Pipedream. They all effectively solve the problem of having one place to put your credentials for the various external services and give your agent a minimal set of tools (to reduce context bloat) that it can use to access them. I want to make clear that this is a good thing, for the short term.
With all the stuff we’ve built around MCP, what we didn’t take into account, or maybe have ignored, is the models getting better. We now have whole systems dedicated to monitoring MCP servers, making sure the responses are good, making sure that agents are able to easily access the tools, figuring out schemas, and determining what we need to give agents so that they can make the right call at the right time.
Surprise, Surprise, the Big Labs Were Right
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