"Dynatrace" matching MCP servers:

This remote MCP server allows interaction with the Dynatrace observability platform. Bring real-time observability data directly into your development workflow.

Enables agents to inspect Kubernetes cluster, node, and pod status, run bounded log searches with surrounding context, triage Davis problems and alerts, query metrics and traces, and review security and compliance summaries. It runs locally over stdio against any Dynatrace SaaS/Grail tenant using configurable connections and filters rather than hardcoded scopes.

A powerful Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to Dynatrace's observability platform. Features dual authentication architecture, Davis CoPilot AI integration, and 24 specialized tools for monitoring, automation, and operational intelligence.

A remote MCP server that enables real-time interaction with the Dynatrace observability platform, bringing production-level monitoring data directly into development workflows.

Provides Model Context Protocol access to the Dynatrace platform API, letting AI agents run live queries against observability, security, and platform data and manage a Dynatrace environment. It is hosted remotely by Dynatrace, so MCP hosts can add it by name from the official registry without installing anything.

Lets AI assistants query Dynatrace Managed environments — services, traces, metrics, pods, and problems — by running read-only GET requests through your already logged-in browser session, so no API tokens are needed. All traffic stays on your machine between the AI client, a local server, and a browser extension.

Enables interaction with Dynatrace Grail and API endpoints by executing DQL queries, retrieving logs, reporting active problems, and querying metrics.

A remote, Dynatrace-hosted MCP server that gives AI agents live API access to your Dynatrace environment. It enables querying and analyzing observability, security, and platform data — such as DQL queries, logs, traces, problems, and dashboards — so agents can act on production context instead of static knowledge.

Enables AI assistants to interact with self-hosted Dynatrace Managed environments to retrieve observability data, security insights, and performance metrics. It allows users to query problems, logs, events, and SLOs through natural language interfaces in both local and remote modes.

Enables LLM agents to query Dynatrace SaaS for observability data (logs, metrics, traces, entities, problems, vulnerabilities) and manage configurations (dashboards, notebooks, SLOs, synthetic monitors, settings).

Enables agents to autonomously investigate deployment health by inspecting Kubernetes resources, comparing live cluster state against Git, and correlating findings with Dynatrace problems.