Debugging agent workflows with MCP observability
As AI agents become more complex, integrating memory, calling external tools, and reasoning over multi-step tasks, debugging them has become increasingly difficult. Traditional observability tools were designed for simple prompt-response flows. But in agentic workflows, failures can occur at any point: a broken tool, stale memory, poor context interpretation, or
