Building MCP Servers on Cloudflare: A Practical Guide
A practical guide to building MCP servers on Cloudflare Workers, covering architecture, code examples with D1 and R2, and production patterns for exposing Cloudflare resources to AI assistants.
A practical guide to building MCP servers on Cloudflare Workers, covering architecture, code examples with D1 and R2, and production patterns for exposing Cloudflare resources to AI assistants.
How to design, build, and ship Model Context Protocol servers that turn LLMs into reliable, tool-using agents — with patterns drawn from Claude Desktop, Cursor, and real production deployments.
Agentic AI is the shift from one-shot prompting to autonomous loops that plan, call tools, observe results, and recover from failure. This guide walks through the core loop, the production patterns, and the infrastructure that makes agents viable at scale.
The next leap in agentic AI isn’t a bigger model — it’s how models talk to each other. Here’s why LLM-to-LLM protocols like MCP and Google’s A2A are replacing the brittle hero-to-API pattern.
Introduction The Model Context Protocol (MCP) is rapidly becoming a foundational layer for connecting AI models to external tools, data sources, and services in a standardized way. As more powerful capabilities are exposed to models—querying databases, sending emails, acting in SaaS systems—authorization becomes a central concern. This article walks through: What MCP is and how resources fit into its design What link resources are and why they matter How link resources are typically used to drive authorization flows Example patterns for building MCP servers that handle auth securely Best practices and common pitfalls The goal is to give you a solid mental model for how MCP authorization with link resources works in practice, so you can design safer, more capable integrations. ...