"Information about Dynatrace (monitoring and observability platform)" matching MCP servers:

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

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

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 interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

Governs and automates network monitoring across SolarWinds Orion and Paessler PRTG platforms with a unified MCP server, enabling querying, alert management, and governed writes with audit logging.

Unified observability gateway for AI agents — one MCP server for Prometheus, Loki, and any backend.

MCP server exposing AI agent observability tools: list, inspect, and deterministically replay recorded agent execution traces for debugging failures.

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).

Unified MCP server for observability and monitoring, providing tools to query metrics, logs, and traces through Prometheus, Grafana, Loki, and Jaeger.

Provides unified AI agent observability including tracing, cost tracking, performance monitoring, anomaly detection, and audit trails via MCP.

Provides comprehensive monitoring and observability for MCP server ecosystems with real-time health checks, performance metrics, distributed tracing, anomaly detection, and automated performance reports using OpenTelemetry and Prometheus.

MCP server for querying observability data from Elasticsearch, SkyWalking, and Prometheus/VictoriaMetrics, enabling AI models to search logs, traces, and metrics across environments.

MCP server for monitoring, diagnosing, and auto-correcting observability issues across platform services, integrating with Sentry and PostgreSQL for error tracking and billing pipeline health.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

A comprehensive Model Context Protocol (MCP) server for Grafana, Prometheus, Kafka UI, and Datadog. Features a secure "Bring Your Own Key" (BYOK) architecture where credentials stay local. Provides tools for metrics querying, dashboard inspection, Kafka lag monitoring, and unified health checks.

Provides AI assistants with direct access to Red Hat OpenShift AI observability data, enabling querying of Prometheus metrics, Alertmanager alerts, Loki logs, Grafana dashboards, and Kubernetes cluster state to troubleshoot vLLM inference workloads.

Provides Claude AI assistants with focused monitoring tools for n8n workflow execution analysis, including active workflow listing, execution history with KPIs, and detailed failure information.

Enables MCP clients to inspect Oracle Integration Cloud integrations, connections, runtime instances, errors, and flow logs through natural-language queries.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.