Dynatrace Managed MCP

Dynatrace Managed MCP Server

Use cases

1. Your Dynatrace Managed environment(s) is/are the primary Observability system, containing all live data; or

2. There has been a migration from a Dynatrace Managed environment to a Dynatrace Saas environment; however, historical observability data has not been migrated and can still be accessed via a Dynatrace Managed environment.

The Dynatrace Managed MCP is used to access historical data, and a separate Dynatrace SaaS MCP is used to access live and more recent data.

Specific use cases for the Dynatrace Managed MCP include:

- Real-time observability - Fetch production-level data for early detection and proactive monitoring

- Contextual debugging - Fix issues with full context from monitored exceptions, logs, and anomalies

- Security insights - Get detailed vulnerability analysis and security problem tracking. This can include multicloud compliance assessment with evidence-based investigation.

- Natural language queries - Queries are mapped to MCP tool usage, and thus API queries, with guidance for the next step

- Multiphase incident investigation - Systematic impact assessment and troubleshooting

- Multienvironment support - Query multiple Dynatrace Managed environments from the same MCP server

Capabilities

- Problems - List and get problem details from your services (for example Kubernetes)

- Security - List and get security problems / vulnerability details

- Entities - Get more information about a monitored entity, including relationship mappings

- SLO - List and get Service Level Objective details, including evaluation and error budgets

- Event Tracking - List and get system events

- Log Investigation - Search and filter logs with advanced content and time-based queries

- Metrics Analysis - Query and analyze performance metrics using V2 Metrics API

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 Code

Claude Code can install this server as a plugin, which skips the manual MCP configuration below and adds a skill covering environment selection and entity selectors. It is published through Anthropic's community plugin marketplace:

/plugin marketplace add anthropics/claude-plugins-community

/plugin install dynatrace-managed-mcp@claude-community

[!IMPORTANT]

The community marketplace listing is pending review. Until it is approved, the install above

reports Plugin "dynatrace-managed-mcp" not found in marketplace "claude-community" - use the

instructions under _Installing straight from this repository_ below in the meantime.

Claude Code prompts for the cluster configuration during install - either the JSON array for a single cluster, or a path to a dt-config.yaml / dt-config.json file for several. See docs/claude-code-plugin.md for details.

[!NOTE]

Third-party marketplaces do not auto-update by default. Run

/plugin marketplace update claude-community to pick up a new plugin version.

Installing straight from this repository instead

This repository is also a plugin marketplace in its own right, which is how you install the plugin before the community listing is approved, try an unreleased change, or pin to a specific branch:

/plugin marketplace add dynatrace-oss/dynatrace-managed-mcp

/plugin install dynatrace-managed-mcp@dynatrace

To configure the server by hand instead, use the Claude Desktop snippet below - it applies to Claude Code's .mcp.json as well.

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 /.kiro/settings/mcp.json, or in user-level settings (~/.kiro/settings/mcp.json).

Google Gemini CLI

Using gemini CLI directly (recommended):

gemini extensions install https://github.com/dynatrace-oss/dynatrace-managed-mcp

export DT_ENVIRONMENT_CONFIGS="[{\"apiEndpointUrl\":\"https://my-api-endpoint.com/\",\"environmentId\":\"my-env-id-1\",\"alias\":\"alias-env\",\"apiToken\":\"my-api-token\"},{\"apiEndpointUrl\":\"https://my-api2-endpoint.com/\",\"environmentId\":\"my-env-id-2\",\"alias\":\"alias-env-2\",\"apiToken\":\"my-api-token-2\"}]"

and verify that the server is running via

gemini mcp list

Or manually