Dynatrace Managed MCP Server

The local Dynatrace Managed MCP server allows AI Assistants to interact with one or more self-hosted Dynatrace Managed deployments, bringing observability data directly into your AI-assisted workflow.

This MCP server supports two modes:

• Local mode: Runs on your machine for development and testing.
• Remote mode: Connects over HTTP/SSE for distributed or production-like setups.

[!TIP] This MCP server is specifically designed for Dynatrace Managed (self-hosted) deployments. For Dynatrace SaaS environments, please use the Dynatrace MCP.

[!NOTE] This open source product is supported by the community. For feature requests, questions, or assistance, please use GitHub Issues.

Quickstart in stdio (local) mode

You can add this MCP server to your AI Assistant, such as VSCode, Claude, Cursor, Kiro, Windsurf, ChatGPT, or GitHub Copilot.

To run this MCP server, you to have to configure four things:

• Dynatrace Managed API token
• Configuration file: dt-config.yaml or dt-config.json file which is responsible for defining list of environments you intend to use
• MCP Server connection configuration file: local mcp configuration, which is dependent on tools you are using
• Set DT_CONFIG_FILE to the path of your dt-config.yaml or dt-config.json file in the MCP server environment.

Dynatrace Managed API token

For information about creating API tokens in Managed deployments, refer to the Dynatrace Managed documentation. Your API token must include the following scopes for full functionality:

• Access problem and event feed, metrics, and topology (DataExport)
• Read entities (entities.read)
• Read events (events.read)
• Read logs (logs.read)
• Read metrics (metrics.read)
• Read problems (problems.read)
• Read security problems (securityProblems.read)
• Read SLO (slo.read)

Configuration File

Configuration parameters

There are two ways to configure your Dynatrace Managed environments.

Method 1: Configuration File (Recommended for Local Development)

Example: dt-config.yaml

# Production environment
- apiEndpointUrl: https://my-api.company.com/
  environmentId: abc-123
  alias: production
  # Token is injected from an environment variable at runtime
  apiToken: ${DT_PROD_TOKEN}
  # You can also use the token directly
  # apiToken: dt0s01.ABCDEFGHIJK0123

# Staging environment
- apiEndpointUrl: https://staging-api.company.com/
  environmentId: xyz-789
  alias: staging
  apiToken: ${DT_STAGING_TOKEN}

Example: dt-config.json

[
  {
    "apiEndpointUrl": "https://my-api.company.com/",
    "environmentId": "abc-123",
    "alias": "production",
    "apiToken": "${DT_PROD_TOKEN}"
  }
]

Method 2: Environment Variable (Docker/Kubernetes)

For Kubernetes deployments or if you prefer environment variables, you can set DT_ENVIRONMENT_CONFIGS with a JSON string in either your .env file or directly in MCP Server connection configuration file

DT_ENVIRONMENT_CONFIGS='[{"apiEndpointUrl":"https://api.example.com/","environmentId":"abc-123","alias":"production","apiToken":"dt0s01.ABCDEFGHIJK0123"}]'

MCP Server connection configuration file

To actually connect to the MCP server you have to configure your MCP connection in your AI Assistant

We recommend always setting it up for your current workspace instead of using it globally.

VS Code

{
  "servers": {
    "npx-dynatrace-managed-mcp": {
      "command": "npx",
      "cwd": "${workspaceFolder}",
      "args": ["-y", "@dynatrace-oss/dynatrace-managed-mcp-server@latest"],
      "envFile": "${workspaceFolder}/.env"
    }
  }
}

Alternatively, this can also be stored in user settings, and you can define env as follows:

{
  "servers": {
    "npx-dynatrace-managed-mcp": {
      "command": "npx",
      "args": ["-y", "@dynatrace-oss/dynatrace-managed-mcp-server@latest"],
      "env": {
        "DT_PROD_TOKEN": "dt0s01.ABCDEFGHIJK0123",
        "DT_CONFIG_FILE": "dt-config.yaml"
      }
    }
  }
}

Claude Desktop

{
  "mcpServers": {
    "dynatrace-managed-mcp": {
      "command": "npx",
      "args": ["-y", "@dynatrace-oss/dynatrace-managed-mcp-server@latest"],
      "env": {
        "DT_PROD_TOKEN": "dt0s01.ABCDEFGHIJK0123",
        "DT_CONFIG_FILE": "dt-config.yaml"
      }
    }
  }
}

Kiro

{
  "mcpServers": {
    "dynatrace-managed-mcp": {
      "command": "npx",
      "args": ["-y", "@dynatrace-oss/dynatrace-managed-mcp-server@latest"],
      "env": {
        "DT_PROD_TOKEN": "dt0s01.ABCDEFGHIJK0123",
        "DT_CONFIG_FILE": "dt-config.yaml"
      }
    }
  }
}

This configuration should be stored in <project-root>/.kiro/settings/mcp.json, or in user-level settings (~/.kiro/settings/mcp.json).

Google Gemini CLI

Using gemini CLI directly (recommended):