AIF-C01 Practice Question 33: Model Context Protocol

AWS Certified AI Practitioner (AIF-C01) · Test 4 · question 3 of 10

Fundamentals of GenAImedium

A company has several teams building AI agents. Each team writes its own custom integration code for the same internal systems, such as the ticketing API and the customer database, so the tools are duplicated, inconsistent, and hard to govern. Every tool change also requires redeploying each agent. What should the company adopt to standardize how its agents discover and call these tools?

Show answer and explanation

Answer:

D. Model Context Protocol (MCP) servers that host the tools for all of the agents

The Model Context Protocol (MCP) is a universal standard for connecting agents to external capabilities, often described as "USB-C for AI applications". Instead of registering tools directly inside each agent, MCP servers host the tools, and agents discover and invoke them in a standardized way. AWS lists the situations where MCP fits: duplicated tools, developers spending too much time on inconsistent custom integrations, and a need for centralized governance over how agents reach enterprise systems. Because MCP decouples agents from the tools they use, a tool can change without redeploying every agent (option D).

- A is wrong because RAG adds *reference information* to a prompt. Reading about the API doesn't let an agent actually call it, and it does nothing to standardize integrations. - B is wrong because tool definitions consume the context window, and cramming more of them in can degrade the model's performance. It also leaves the duplicated integration code in place. - C is wrong because fine-tuning changes a model's weights. It doesn't give agents a shared, governed way to connect to live systems, and the tools would still be rebuilt by each team.

Reference: What is MCP?

Practice Test 4 ›

Study guides for AIF-C01

AI engineer roadmap 2026: skills, certs and the orderAI engineer roadmap for 2026: skills to learn in order, AI engineer vs ML engineer, which certifications fit each stage, and what to skip.

How AI Is Changing Software Jobs: Where to PrepareHow AI is changing software jobs: what history shows, the evidence on junior developers, what Klarna learned, new AI roles and five domains to prepare for.

How AWS Certification Exams Work: Scoring and RenewalHow AWS certification exams work: levels, booking, question types, unscored questions, scaled scores, pass marks, validity and how recertification works.

What Is Amazon Bedrock? Models, Pricing and GuardrailsWhat is Amazon Bedrock? How a request reaches a model, what happens to your data, token pricing, Guardrails, Knowledge Bases, AgentCore and the exam traps.

Google Cloud Generative AI Leader vs AWS AI PractitionerGoogle Cloud Generative AI Leader vs AWS AI Practitioner: format, cost, topics, free preparation and which certification to take first.

AWS certification cost in 2026, and free ways to prepareWhat every AWS certification costs in 2026 in USD and INR, retake and reschedule rules, the 50% voucher, and the free official ways to prepare.

AWS Generative AI Developer Professional (AIP-C01) guideWhat the AWS Certified Generative AI Developer – Professional (AIP-C01) exam covers - format, cost, the five domains, the services, and how to prepare.

Best AI certifications 2026: AWS, Google, Microsoft, ClaudeThe best AI certifications in 2026 from AWS, Google, Microsoft, Claude and Databricks, by level, with price, status and which one to take first.

Which AWS certification should you get? 2026 roadmapWhich AWS certification to get first, by role and experience, with each exam's status in October 2026, what is changing, and prices in USD and INR.

What Is RAG? How Retrieval-Augmented Generation WorksWhat RAG is and how it works: chunking, embeddings, vector search, hybrid search, reranking, GraphRAG and agentic RAG on AWS, Google and Azure.

Prompt engineering vs RAG vs fine-tuningWhen to use prompt engineering, retrieval-augmented generation, fine-tuning or continued pre-training, compared on cost, freshness, hallucination and privacy.