Understanding Google MCP

What Is MCP?

The Model Context Protocol (MCP) is an open standard that defines how large language models interact with external tools, data sources, and applications.

It gives AI models a universal interface to discover tools, call functions, read/write data, and perform actions—using a consistent, structured protocol.

The Problem MCP Solves

Traditionally, every AI integration required custom APIs or ad-hoc glue code. MCP solves this by creating a standard communication layer, powered by JSON-RPC, that works across different environments, languages, and LLM providers.

Key Concept

In short: MCP turns LLMs into reliable, tool-using agents, not just text generators.

Instead of being limited to generating text, LLMs can now:

• Discover tools available in their environment
• Call functions to perform actions
• Read and write data from various sources
• Interact with applications through a standardized interface

Technical Foundation

MCP is built on JSON-RPC, a lightweight remote procedure call protocol that enables:

• Structured communication between AI models and tools
• Cross-platform compatibility (works across different languages and environments)
• Provider-agnostic design (works with OpenAI, Anthropic, Google, and local models)

Why This Matters

Before MCP, integrating AI capabilities into applications meant:

• Building custom APIs for each LLM provider
• Writing different integration code for OpenAI, Anthropic, Google, etc.
• Maintaining multiple code paths for similar functionality
• Limited interoperability between AI systems

With MCP, you get:

• One standard interface for all LLM providers
• Reduced boilerplate and integration complexity
• Better interoperability between AI systems
• A foundation for AI-native applications