Build and Deploy a Remote MCP Server to Google Cloud Run in Under 10 Minutes

Integrating context from tools and data sources into LLMs can be challenging, which impacts ease-of-use in the development of AI agents. To address this challenge, Anthropic introduced the Model Context Protocol (MCP), which standardizes how applications provide context to LLMs. Imagine you want to build an MCP server for your API to make it available to fellow developers so they can use it as context in their own AI applications. But where do you deploy it? Google Cloud Run could be a great option.

Drawing directly from the official Cloud Run documentation for hosting MCP servers, this guide shows you the straightforward process of setting up your very own remote MCP server. Get ready to transform how you leverage context in your AI endeavors!

MCP Transports

MCP follows a client-server architecture, and for a while, only supported running the server locally using the stdio transport.

MCP ...