In the rapidly evolving landscape of AI, protocols like Google's Agent-to-Agent (A2A) and Anthropic's Model Context Protocol (MCP) are emerging as key enablers for building sophisticated AI systems. Understanding the differences between these protocols is crucial for making informed decisions about which one best suits your project's needs. This post will break down the core distinctions between A2A and MCP to help you choose the right tool for the job.

Agent workflows have quickly emerged as one of the most compelling frontiers in AI application development—but building them for real-world production use cases is still a nuanced and evolving challenge. At Stride, we recently partnered with a healthcare client to redesign a complex patient-facing workflow using LangGraph, LangChain’s graph-based orchestration framework.

Claude Code represents a fascinating approach to AI-assisted development, leveraging powerful language models through command-line tools and file manipulation. However, this architecture creates an interesting trade-off compared to editor-native AI assistants, particularly when it comes to tasks that modern IDEs handle through built-in tooling.