The agentic experience: Is MCP the right tool for your AI future?

As enterprises strive to operationalize AI, integrating large language models (LLMs) into existing API ecosystems while ensuring security, governance, and compliance is a significant challenge. Apigee, Google Cloud's API management platform, plays a crucial role in this integration process by enhancing the security, scalability, and governance of gen AI agents within applications. The Model Context Protocol (MCP) has become a prominent method for integrating discrete APIs, yet its rapid evolution means it doesn't fully address enterprise needs for authentication, authorization, and observability. Apigee provides an open-source example of an MCP server with robust API security features, demonstrating how enterprises can leverage these tools to secure, scale, and govern their AI interactions. This setup bridges the gap between managed APIs and exploratory AI interactions, making it adaptable to changes in the MCP standard. Apigee offers a GitHub repository with resources to guide users in deploying the reference MCP Serving architecture, emphasizing its commitment to evolving alongside the AI landscape and supporting enterprises in their AI journeys.

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