Since the Datadog Model Context Protocol (MCP) Server first launched in Preview, Datadog has experienced an overwhelming amount of interest and feedback from customers. We appreciate those who requested access to test our product, provided feedback, and shared their stories of how the MCP Server helped them overcome engineering challenges.

We’re excited to announce that the Datadog MCP Server is now generally available. The Datadog MCP Server connects Datadog tools and context with AI agents that developers use in their everyday workflows such as Claude Code, Cursor, Codex, Goose, GitHub Copilot, Cognition, Visual Studio Code, and Kiro. But our MCP Server isn’t just limited to real-time prompting by developers. It can also be used to provide background agents with the data they need to solve problems specific to your engineering organization.

In this blog post, we’ll highlight a few customer use cases where agents use the Datadog MCP Server to automate processes and remove previous points of friction in developer workflows. These examples will show how the MCP Server can help you:

Onboard Datadog products and best practicesAutomatically detect and shut down unused servicesCorrelate incidents with feature flag changesDetect anomalous cloud costs