Improve your AI coding agent with runtime context from Aspire MCP

This article explains why AI coding agents need runtime context to make better suggestions, focusing on Aspire MCP. It discusses how modern applications composed of APIs, databases, message brokers, and containers require understanding beyond source code. The article covers the runtime context stack, including OpenTelemetry for observability (logs, traces, metrics), Aspire for local orchestration and application modeling, and AI agents that leverage this context for improved assistance. It highlights scenarios like analyzing logs to find errors, identifying performance issues, and pinpointing failures, showing how combining these tools yields more accurate insights than source code alone.