Introduction to the Model Context Protocol
Generative AI has rapidly become a force in today’s technological landscape, reshaping industries and redefining how we approach problem-solving. From natural language processing to image generation, the integration of generative AI into various domains has opened up new possibilities for innovation and efficiency.
For us developers, integrating generative AI into app development workflows is not without its complexities. We must carefully evaluate factors such as model accuracy, ethical considerations, and computational efficiency.
It’s in the process of building applications that we need to consider how we standardize the way we build our AI applications. Standardization means that everything looks the same, which should mean easier integration and collaboration across different teams and tools.
This is where the Model Context Protocol (MCP) comes in, to standardize how we ensure that AI-powered applications can easily find what they need from tools, content, and prompts; more on that shortly.
The chapter covers the following topics:
- How we got here, from SOAP to REST to GraphQL to gRPC to MCP
- The need for a standard
- Endless possibilities: know how to prompt, and a world of MCP servers is your oyster
- What is the MCP?
