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About Datadog MCP Server

Datadog MCP Server bridges your Datadog observability platform with AI assistants through the Model Context Protocol. It gives LLMs like Claude structured access to metrics, logs, monitors, SLOs, service definitions, CI/CD pipelines, and team information, enabling natural language queries against your monitoring infrastructure. The server provides 12 core tools: listing and querying metrics with flexible aggregation and grouping, fetching service logs filtered by environment and time range, managing monitors and SLOs, retrieving service definitions with ownership metadata, listing CI pipelines with fingerprint extraction for Terraform, and viewing teams with member details. Each tool supports multiple output formats and filtering options. Available as an open-source npm package, the server connects to the Datadog API using your API and application keys. Datadog also offers official MCP Server documentation and LLM Observability features that trace MCP client calls with structured metadata about invoked tools, parameters, and responses. The server works with Claude Desktop, Claude Code, Cursor, and other MCP-compatible clients, making it straightforward to investigate incidents, analyze metrics, or review service health through conversational AI.