Universal Containers is building a digital shopping assistant that needs to dynamically generate product recommendations...

Per the AgentForce Integration and AI Architecture Guide, the Model Context Protocol (MCP) enables agents to interact dynamically with external predictive or AI models. The documentation states:

“Through MCP, agents can discover, connect, and invoke external models via standardized schema definitions. This allows agents to use third-party tools—like recommendation engines or classifiers—without pre-coding fixed API calls.”

Option A (MCP) supports dynamic interoperability with predictive models, making it the correct answer.

Option B (Hugging Face) refers to a model hosting platform, not a Salesforce integration mechanism.

Option C (A2A protocol) supports agent-to-agent communication, not external model invocation.

Therefore, Option A correctly reflects the Salesforce-recommended method for integrating external predictive APIs.

References (AgentForce Documents / Study Guide):

AgentForce Architecture Guide: “Integrating Predictive Models with MCP”

AgentForce Technical Overview: “Model Context Protocol for External Tools”

AgentForce Study Guide: “Using MCP for Recommendation and AI Model Access”