In the second installment of the “Agent Factory” series, we dive into how the effectiveness of agents is directly linked to the tools and governance frameworks they utilize. Following a discussion on five key design patterns of agentic AI, the focus shifts to the industry’s transition from static models to extensible systems. Open protocols like the Model Context Protocol (MCP) are highlighted for enhancing tool integration, making them portable and interoperable across various environments.
Azure AI Foundry supports MCP, offering built-in tools for rapid deployment, custom tool creation for unique business needs, and extensive connectors for integrating with existing systems. Emphasizing security and observability, enterprise-grade governance is essential for managing these tools effectively.
Key principles for success include establishing clear contracts for tools, centralizing governance, and ensuring strong identity management. This approach guarantees that agent ecosystems remain secure, agile, and maintainable as they evolve. Stay tuned for part three, focusing on observability for AI agents.
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