My coding agent kept "fixing" proxy errors wrong, so I built an MCP server

<p>A directory result, a GitHub repository and an install command can all have similar names. They are not necessarily the same artefact. Before you add an MCP server to a client,

<p>MCP is one of the most thoughtfully scoped technical standards to come out of the AI ecosystem. That scope is intentional. Understanding exactly where MCP stops is the

<p>REST APIs gave humans (and the code they wrote) a standardized way to access software over the network.</p> <p>MCP is trying to do the same thing for agents.</p> <p>That simple

<p>Most API documentation is written for humans.</p> <p>MCP tool descriptions are different.</p> <p>They are read by the model that decides what to call next.</p> <p>That means

<p>The AI world has a plumbing problem. We have incredible language models, but connecting them to real tools — databases, APIs, file systems, other agents — still feels like

<!-- SC_OFF --><div class="md"><p>The basic idea is simple: if you have an OpenAPI REST API, it makes it useable by AI agents with a single command without writing a MCP server

<h1> I Built a Pay-Per-Use MCP Server with 52+ Services </h1> <p>Every MCP server I found was either free (good luck scaling), subscription-based (hello, vendor lock-in), or

<h2> The Problem </h2> <p>The MCP ecosystem is expanding at an extraordinary pace. Anthropic, Microsoft, Google, AWS, and Cloudflare are all publishing official MCP servers.