Fundamentals of Generative AI A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.
A software company has built five AI agents for support, code review and release planning.
Each agent needs the same ticketing system, code repository and internal wiki, and today every agent has its own custom connector to every tool. The team wants one open protocol so each tool is connected once and any compatible agent can use it.
Which standard addresses this?
Choose one answer.
AA. Model Context Protocol (MCP), an open protocol for connecting AI applications to tools and data sources.
BB. Retrieval Augmented Generation (RAG), which adds retrieved documents to the prompt at query time.
CC. Reinforcement learning from human feedback (RLHF), which tunes a model using ratings from human reviewers.
DD. Open Neural Network Exchange (ONNX), which moves trained models between frameworks and runtimes.
B. Wrong: RAG supplies relevant documents to a model at query time. It does not define how agents connect to ticketing systems or repositories.
C. Wrong: RLHF is a training method that aligns a model with human preferences. It does not connect agents to tools.
D. Wrong: ONNX is a format for moving trained models between frameworks. It does not standardize how agents call external tools.
Explanation
The Model Context Protocol is an open protocol that connects LLM applications to external data sources and tools, so integrations can be built once and reused. RAG, RLHF and ONNX each solve a different problem in the AI stack. This question tests recognizing the standard for agent-to-tool connections.
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