Dynatrace MCP Server Integration

What does “Dynatrace” MCP Server do?

The Dynatrace MCP (Model Context Protocol) Server is a remote MCP server that integrates the Dynatrace observability platform into your AI-powered development workflows. By connecting to Dynatrace, the server enables AI assistants and clients to fetch real-time observability data, production-level metrics, logs, anomalies, and security events directly into the development environment. This enhances issue detection and troubleshooting, enables natural language querying of logs, and provides detailed insights for debugging or securing applications. The Dynatrace MCP Server acts as a bridge between AI agents and the rich monitoring capabilities of Dynatrace, empowering developers to automate diagnostics, trigger workflows, and streamline operations using AI-driven tools.

List of Prompts

No prompt templates are mentioned in the available documentation.

List of Resources

No explicit list of MCP resources is mentioned in the available documentation.

List of Tools

• List and get problem details from your services (e.g., Kubernetes)
• List and get security problems/vulnerability details
• Execute Dynatrace Query Language (DQL) to get events or logs
• Send Slack messages via Slack Connector
• Set up notification workflows via Dynatrace AutomationEngine
• Get ownership information of an entity

Use Cases of this MCP Server

• Real-time Observability Data
  Fetch production-level metrics and logs from Dynatrace to identify and resolve issues quickly during development.
• Incident and Exception Resolution
  Bring monitored exceptions, logs, and anomalies directly into your workflow to fix issues with all relevant context.
• Security Issue Context
  Retrieve detailed security and vulnerability information for your services, helping to address and remediate threats efficiently.
• Natural Language Querying of Logs
  Use natural language to query log data and events, making observability accessible to a wider range of team members.
• Automated Notifications and Workflows
  Set up notification workflows and send Slack messages to teams for immediate action on detected problems or vulnerabilities.

How to set it up

Windsurf

1. Ensure Node.js is installed and available in your environment.
2. Open Windsurf’s configuration file for MCP servers.
3. Add the Dynatrace MCP Server using the following JSON snippet:

   {
     "servers": {
       "npx-dynatrace-mcp-server": {
         "command": "npx",
         "args": ["@dynatrace-oss/dynatrace-mcp-server@latest"]
       }
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify the server connection within Windsurf’s MCP interface.

Claude

1. Ensure Node.js is installed.
2. Locate Claude’s MCP server configuration file.
3. Insert:

   {
     "servers": {
       "npx-dynatrace-mcp-server": {
         "command": "npx",
         "args": ["@dynatrace-oss/dynatrace-mcp-server@latest"]
       }
     }
   }
   

4. Save the file and restart Claude.
5. Check the MCP server connection in Claude’s settings.

Cursor

1. Install Node.js if not already present.
2. Access Cursor’s MCP server configuration.
3. Add:

   {
     "servers": {
       "npx-dynatrace-mcp-server": {
         "command": "npx",
         "args": ["@dynatrace-oss/dynatrace-mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration, then restart Cursor.
5. Validate the Dynatrace MCP connection.

Cline

1. Make sure Node.js is installed.
2. Open Cline’s JSON configuration for MCP servers.
3. Enter:

   {
     "servers": {
       "npx-dynatrace-mcp-server": {
         "command": "npx",
         "args": ["@dynatrace-oss/dynatrace-mcp-server@latest"]
       }
     }
   }
   

4. Save changes and restart Cline.
5. Confirm the MCP server is active.

Securing API Keys

Store sensitive credentials (e.g., Dynatrace API keys) in environment variables and reference them in your configuration.
Example:

{
  "servers": {
    "npx-dynatrace-mcp-server": {
      "command": "npx",
      "args": ["@dynatrace-oss/dynatrace-mcp-server@latest"],
      "env": {
        "DYNATRACE_API_KEY": "${DYNATRACE_API_KEY}"
      },
      "inputs": {
        "apiKey": "${DYNATRACE_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "dynatrace-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “dynatrace-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Short review: The Dynatrace MCP Server offers strong integration for observability and monitoring tasks, with clear setup instructions and tool exposure. However, the absence of documented prompts, explicit resources, roots, and sampling support limits its completeness as an MCP package.

MCP Score

Rating: 7/10
The Dynatrace MCP Server is solid for observability integration, but lacks documentation on prompts, resources, roots, and sampling, which prevents a higher score.