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@kud/mcp-datadog

Datadog MCP server for monitoring, metrics, logs, and dashboards

Monitoring & Observability
Install Command
npx -y @kud/mcp-datadog
Claude Desktop Config
{
  "mcpServers": {
    "kud-mcp-datadog": {
      "command": "npx",
      "args": [
        "-y",
        "@kud/mcp-datadog"
      ]
    }
  }
}

@kud/mcp-datadog is a community MCP server that connects AI assistants like Claude to datadog mcp server for monitoring, metrics, logs, and dashboards. 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 @kud/mcp-datadog

Overview

Datadog MCP server for monitoring, metrics, logs, and dashboards

Links

Topics

datadog, mcp, mcp-server, monitoring, metrics, logs, observability

Who Should Use @kud/mcp-datadog?

  • 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 @kud/mcp-datadog

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 @kud/mcp-datadog Compares

It runs entirely on your local machine, so no data leaves your environment — important for teams with privacy or compliance requirements.
It is distributed as an npm package, making version management and updates straightforward with a single `npm update` command.

Tags

datadogmonitoringmetricslogsobservability

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