Datadog - OpenClaw Skill — OpenClaw Tutorials

Install Command

npx clawhub@latest install datadog

Installation Guide

Check Environment

Make sure Node.js 22+ and OpenClaw are installed. Run openclaw --version in your terminal to verify.

Run Installation

Run the install command above in your terminal. ClawHub will automatically download and install Datadog to the ~/.openclaw/skills/ directory.

Verify Installation

Run openclaw skills list to check your installed skills and confirm Datadog appears in the list.

Configure (Optional)

Follow the configuration instructions in the description below to add skill settings to ~/.config/openclaw/openclaw.json5.

Manual Installation: Copy the Skill folder to ~/.openclaw/skills/ or the skills/ directory in your project root. Make sure the folder contains a SKILL.md file.

Monitoring metrics querying and visualization Log search and analysis Event and alert management

Detailed Description

Datadog MCP server brings Datadog's full-stack observability capabilities into AI conversations, enabling direct querying of monitoring metrics, log searching, and alert management to help teams discover and resolve production issues faster.

Core Features

Metrics Query (query_metrics): Query various monitoring metrics using Datadog query syntax, with support for aggregation, grouping, and time range configuration
Log Search (search_logs): Search for specific events in Datadog logs, supporting full-text search and facet filtering
Dashboard Management: List and view dashboard information, get monitoring panel configurations and visualization data
Event Management: Query and create Datadog events to mark important timepoints like deployments and incidents
Alert Monitoring (get_monitors): View alert rule statuses and identify currently triggering alerts

Configuration

{
  "mcpServers": {
    "datadog": {
      "command": "npx",
      "args": ["-y", "@datadog/mcp-server"],
      "env": {
        "DD_API_KEY": "your-api-key",
        "DD_APP_KEY": "your-app-key",
        "DD_SITE": "datadoghq.com"  // Or datadoghq.eu, etc.
      }
    }
  }
}

Use Cases

Incident troubleshooting: Search logs and metrics to identify the root cause of production issues
Performance optimization: Query APM metrics to identify slow requests and bottlenecks
Capacity planning: Analyze resource usage trends to predict scaling needs
Deployment monitoring: View key metric changes in real-time after deployments

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