How to Build AI Agents with the Claude Agent SDK and Firecrawl

The tutorial describes how to use the Claude Agent SDK to create a Python-based dependency auditor that evaluates package health from PyPI and GitHub, utilizing the Firecrawl MCP server to facilitate web research. It outlines the setup process, including defining Pydantic models for structured audit output and creating an orchestrator agent that manages parallel subagents tasked with data scraping. The SDK allows for the automation of tasks typically performed interactively via the Claude Code CLI tool, making it suitable for integration into scripts or pipelines. Key features include subagent parallelism, structured JSON output, and MCP server integration for enhanced web data retrieval. The tutorial emphasizes the importance of system prompts to tailor agent behavior and provides insights into managing errors and debugging. It also highlights the SDK's alpha status, advising users to pin versions due to potential breaking changes. The process culminates in generating a color-coded terminal report sorted by risk level, with a markdown report saved alongside the input requirements file.