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Datadog MCP

Query Datadog metrics, logs, traces, and dashboards

Official
Featured
Monitoring & Observability
Install Command
npx -y @datadog/mcp-server
Claude Desktop Config
{
  "mcpServers": {
    "datadog": {
      "command": "npx",
      "args": ["-y", "@datadog/mcp-server"],
      "env": { "DD_API_KEY": "<KEY>", "DD_APP_KEY": "<APP_KEY>", "DD_SITE": "datadoghq.com" }
    }
  }
}

Datadog MCP is an officially maintained MCP server in the Monitoring & Observability category, developed by Datadog. It runs locally on your machine, keeping your data private and giving you full control over the connection. Adding it to your setup expands what Claude can do without any extra coding.

About Datadog MCP

Official Datadog MCP server connecting AI agents to Datadog's unified observability platform.

Features

  • Query metrics with advanced filters
  • Search and tail logs in real time
  • Access distributed traces
  • View and manage dashboards
  • Create and manage monitors/alerts
  • Incident management

Who Should Use Datadog MCP?

  • 1Extend Claude and other AI assistants with new capabilities
  • 2Automate tasks that previously required manual steps
  • 3Connect your existing tools to an AI workflow
  • 4Reduce repetitive work by letting AI interact with your services

How to Install Datadog MCP

Before you start

You will need Node.js (v18 or later) installed on your machine — download it from nodejs.org if you haven't already.

  1. 1Open a terminal (Terminal on Mac, Command Prompt or PowerShell on Windows).
  2. 2Paste the install command above and press Enter — Node.js will download and run the server automatically.
  3. 3Add the server to your Claude Desktop config file (see the JSON snippet above) and restart Claude.

The Claude Desktop config snippet above can be copied and pasted directly into your claude_desktop_config.json file — no editing required.

How Datadog MCP Compares

It is an officially maintained server — unlike community alternatives, it is built and supported by the original project team, ensuring compatibility with upstream changes.
It runs entirely on your local machine, so no data leaves your environment — important for teams with privacy or compliance requirements.
Authentication uses API keys, giving you fine-grained control over access without requiring a full OAuth setup.

Tags

datadogmonitoringlogsmetricsobservability