What Breaks MCP Servers in Production (MCP Best Practicies)?

<p>If you've shipped a <a href="https://modelcontextprotocol.io" rel="noopener noreferrer">Model Context Protocol</a> server, you've probably hit this: the server <em>works</em>

<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>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

<p><em>Part 6 of the MCP in Practice Series · Back: <a href="https://dev.to/gursharansingh/build-your-first-mcp-server-and-client-bhh">Part 5 — Build Your First MCP Server (and

<h1> Remote MCP Uptime Is Not Production Readiness </h1> <p>A remote MCP server that responds is not necessarily a remote MCP server you should trust in production.</p> <p>That

<p><em>Originally published at <a href="https://webofmike.com/shadow-mcp-servers/?utm_source=devto&amp;utm_medium=syndication&amp;utm_campaign=shadow-mcp-servers" rel="noopener

<h1> MCP Best Practices: 7 Hard Lessons I Learned Building 5 MCP Servers (Full Checklists Included) </h1> <p>Let me be honest with you — I've built five different MCP (Model