This chapter covers
- The Model Context Protocol (MCP) and why it is important for building modern web applications powered by large language models
- Integrating the MCP with the Vercel AI SDK to extend web apps with external capabilities
- Practical examples of building and connecting an MCP server
- Developing a complete end-to-end project to integrate an MCP server
- Introducing the MCP architecture, data flow, and integration patterns
The game-changing Model Context Protocol (MCP) is a new open standard designed to connect AI agents with external tools and data sources in a secure and standardized way.
Designed and open sourced by Anthropic (https://mng.bz/oZqy), the MCP defines a server protocol for exposing tools, prompts, and resources to AI models. It’s rapidly gaining traction because it simplifies the process of extending applications with external functionality and enables interoperability across ecosystems.
Any client that implements this protocol, whether a server application, browser-based web app, or CLI tool, can interact consistently with MCP servers. This means the AI agent, wherever it runs, always knows how to call a tool and handle its outputs, whether that tool accesses an API, a database, or a filesystem. In short, adding MCP capabilities to your applications allows them to tap into the many tools and databases that others create, provided those tools are also MCP compatible.