MCP Integration in Claude Code: Scopes, Resources and Built-in Tools
Configure MCP servers in Claude Code at project or user scope with env variables, use resources for catalogues, and pick Grep, Glob, Read, Edit or Write.
Online Learning Platform
Free tutorials, solved practice problems and interview prep for QA and automation engineers: Python, Playwright, Selenium, SQL, Git and more.
Configure MCP servers in Claude Code at project or user scope with env variables, use resources for catalogues, and pick Grep, Glob, Read, Edit or Write.
Return structured MCP tool errors to Claude with isError, error categories and retryable flags, and learn why an empty result is not a failure.
Write Claude tool descriptions that stop misrouting, give each agent the right tools, and use tool_choice auto, any or forced selection correctly.
Choose prompt chaining or dynamic decomposition, split reviews into per-file and integration passes, and pick resume, fork or fresh start in Claude Code.
Use Claude Agent SDK hooks and prerequisite gates for rules that must always hold: block risky tool calls, normalise tool results and hand off to humans.
Design coordinator and subagent systems with the Claude Agent SDK: Task tool, allowedTools, explicit context passing, parallel subagents and decomposition.
Build a correct Claude agentic loop: check stop_reason, run tool_use blocks, return tool_result messages and avoid the termination traps the exam tests.
The six CCAR-F scenarios explained: support agent, Claude Code, multi-agent research, developer tools, CI/CD and data extraction. Know what each tests.
CCAR-F exam guide: 60 items in 120 minutes, 4 of 6 scenarios, five weighted domains, scoring, registration and out-of-scope topics. Study the right things.
Compare all four Anthropic Claude certifications: format, cost, passing score, who can sit them and which to take first. Plan your certification path now.
Run a full QA mock interview with AI, learn the ethical rules for using AI in interviews and at work, and create your final review plan for this…
Prepare for an AI system design interview by designing a QA agent step by step, covering requirements, components, safety, evaluation, cost and failures.
Take free timed mock tests with answers and explanations.