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Anthropic CCAR-F Exam Dumps Questions and Answers

Exam Code: CCAR-F
Exam Name: Claude Certified Architect – Foundations
Certification: Claude Certified Architect
Vendor: Anthropic
Last Update: Jul 17, 2026
Questions: 60 With Expert Explanation
10  Customers Passed Anthropic CCAR-F
86%  Average Success In Real Exam
92%  Questions came word by word from this dump
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Anthropic Related Certification Exams

Claude Certified Architect – Foundations Questions and Answers

Questions 1

You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.

After integrating a local MCP server providing code analysis tools ( analyze_dependencies , find_dead_code , calculate_complexity ), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies —even when users explicitly ask about “code dependencies.” Examining tool definitions reveals:

    MCP analyze_dependencies – “Analyzes dependency graph”

    Built-in Grep – “Search file contents for a pattern using regular expressions. Returns matching lines with line numbers and surrounding context.”

What’s the most effective approach to improve the agent’s selection of MCP tools?

Options:

A.

Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.

B.

Expand MCP tool descriptions to detail capabilities and outputs—e.g., “Builds dependency graph showing direct imports, transitive dependencies, and cycles.”

C.

Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.

D.

Split analyze_dependencies into granular tools ( list_imports , resolve_transitive_deps , detect_circular_deps ) so each has a focused purpose less likely to overlap with Grep.

Questions 2

You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.

Your codebase exploration tool stores session IDs to allow engineers to continue investigations across work sessions. An engineer spent an hour yesterday analyzing a legacy authentication module, building context about its architecture and dependencies. They want to continue today. The session ID is valid, but version control shows 3 of the 12 files the agent previously read were modified overnight by a teammate’s merge.

What approach best balances efficiency and accuracy?

Options:

A.

Start a fresh session to ensure the agent works with current codebase state without stale assumptions

B.

Resume the session and inform the agent which specific files changed for targeted re-analysis

C.

Resume the session and immediately have the agent re-read all 12 previously analyzed files

D.

Resume the session without informing the agent about the changed files

Questions 3

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.

Your system must extract event details from calendar invitations and output JSON that strictly conforms to a schema with fields for title, date, time, location, and attendees. Downstream systems reject any malformed or non-conformant JSON.

What approach provides the most reliable schema compliance?

Options:

A.

Pre-fill Claude’s response with an opening brace to force JSON output, then complete and parse the response.

B.

Append instructions like “Output only valid JSON matching the schema exactly” and implement retry logic to re-prompt when JSON parsing fails.

C.

Define a tool with your target schema as input parameters and have Claude call it with the extracted data.

D.

Include detailed JSON formatting instructions and the target schema in your prompt, then parse Claude’s text response as JSON.

Next Question