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Bring Dynatrace observability data into development for troubleshooting and performance analysis.
This MCP tool has limited documentation, but it is open source under MIT and does not declare required local secrets or specific remote endpoints. No concrete high-risk red flags are evident; the main concerns are its code-execution capability and the limited disclosure around its actual network and data boundaries when interacting with Dynatrace.
The material explicitly states “required secrets/environment variables: none,” and there is no indication that users must provide API keys, tokens, or local sensitive credentials; based on the available facts, credential exposure appears low.
The description says it “allows interaction with the Dynatrace observability platform,” which implies expected outbound network communication; however, no specific host or data-flow details are provided, so the actual destinations and transmitted content should be verified.
The system checks explicitly mark this tool as having code-execution capability, meaning it runs a local service or related code in the host environment. This is common for MCP tools; no evidence shows privilege escalation or suspicious execution beyond its stated purpose, but it should still be run with least privilege.
Based on the description, the tool is intended to access real-time observability data from Dynatrace and may handle monitoring, logs, metrics, or traces; however, the missing README leaves local file access, caching behavior, and scope restrictions undocumented.
Positive signals include that the project is open source, auditable, and MIT-licensed; however, it comes from a third-party registry, has 0 stars, and has unknown maintenance status, so public trust signals are limited and source/dependency review is advisable before installation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "dynatrace-mcp" yet — see the docs or source repo.
Connect to Dynatrace and analyze why the order API latency increased in the past 2 hours. Identify the most impacted services, abnormal time windows, related error metrics, and suggest next troubleshooting steps.
A latency investigation summary with key services, abnormal metrics, time ranges, and troubleshooting recommendations.
Using Dynatrace data, compare error rate, response time, and resource usage for 1 hour before and after this release. Determine whether there is regression risk and provide a conclusion.
A post-release health report describing metric changes, possible regressions, and whether rollback is recommended.
Fetch the last 24 hours of core observability data for the payment service from Dynatrace and summarize throughput, error rate, average response time, and notable incidents.
A concise service performance overview for the team to quickly understand system health and anomalies.
Query Dynatrace observability data and manage monitoring configurations and reliability assets.
Query Dynatrace logs, metrics, problems, and vulnerabilities for faster troubleshooting.
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