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Anthropic CCAR-P Exam Syllabus Topics:

Anthropic Claude Certified Architect - Professional Sample Questions:

1. You are compiling factors that should drive the choice between Model Context Protocol (MCP), direct API integration, and agent-to-agent handoff.
Which two factors belong on the list? (Select two.)
Each correct answer presents a complete solution.

A) Whether the integration must be portable across multiple AI clients in the ecosystem.
B) Whether the underlying transport supports encryption in transit between the integrated services.
C) Whether the team has prior implementation experience with any of the candidate protocols.
D) Whether the vendor publishes detailed reference documentation for each candidate protocol.
E) Whether the interaction is stateless and latency-sensitive or stateful and longer-running.

2. You are building an ethics-review checklist for deployments supported by artificial intelligence.
Which two checks belong on the list? (Select two.)
Each correct answer presents a complete solution.

A) Verify that outputs do not rely on generalizations about people that the underlying data does not support.
B) Restrict ethics review to outputs that exceed a defined model-confidence threshold.
C) Confirm that latency and throughput targets are met across supported user populations.
D) Confirm that vendor licensing terms permit the planned production use of the model.
E) Confirm that high-impact decisions retain human accountability rather than being attributed to the model.

3. You are a solution architect designing a Claude-based assistant with access to 60 internal tools across multiple business domains. Loading every tool definition on every request increases token usage and time to first response.
Which design pattern best addresses this issue without sacrificing capability breadth?

A) Apply progressive tool discovery so a curated initial subset is exposed and additional tools are loaded on demand based on the task.
B) Increase the maximum context length and load all 60 tool definitions on every request, accepting the higher token cost and latency as necessary for full capability.
C) Hard-code a fixed set of five tools per request to reduce token usage, regardless of whether those tools are relevant to the current task.
D) Use a separate model call to summarize all 60 tool definitions before each user turn.

4. You are selecting a protocol for a single low-latency stateless tool call from a Claude-based assistant to an internal pricing service that already exposes a stable HTTP API.
Which integration mechanism is the most appropriate?

A) A long-lived stateful session protocol for a stateless single-call interaction.
B) An agent-to-agent handoff that introduces another Claude-based agent in front of the pricing service.
C) A bespoke streaming protocol layered over an unrelated asynchronous message bus.
D) A direct API call to the existing endpoint with the appropriate scoped credentials.

5. You are designing a content moderation classifier that processes high volumes of user-generated comments under a tight per-message latency budget using well-defined classification labels.
Which model selection best aligns with the workload?

A) Opus, because every moderation decision requires maximum reasoning depth regardless of classification complexity.
B) Haiku, because its latency and cost profile align with high-volume classification workloads that require limited reasoning depth.
C) Sonnet, because larger general-purpose models are preferred even when workload latency requirements are strict.
D) Sonnet with extended thinking enabled, because deeper reasoning should be applied to every moderation request to improve edge-case handling.

Solutions: