observability_metric_anomaly_detector
As a CTO, quickly identify anomalous cloud metrics (CPU, latency, memory) by comparing your infrastructure against AWS public benchmarks and CVE-linked hardware risks. Input your observed metrics (e.g., CPU utilization, request latency) and receive a risk assessment with potential root causes. Id...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/observability-metric-anomaly-detector.md
What observability_metric_anomaly_detector does on Gapup Mcp
AI agents call observability_metric_anomaly_detector to retrieve information from Gapup Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
region | string | — | |
metricType | string | Yes | |
instanceType | string | — | |
observedValue | number | Yes |
Parameters from the server's own tool schema.
Why observability_metric_anomaly_detector is rated Low
The tool reads and analyzes input metrics, compares them against public benchmarks, and returns a risk assessment. It does not modify, execute, delete, or trigger any external operations — it is purely a read/query/analysis tool. Severity is low as misuse would at most result in misleading diagnostic output.
From the tool's definition identify anomalous cloud metrics (CPU, latency, memory) by comparing your infrastructure against AWS public benchmarks and CVE-linked hardware risks... receive a risk assessment with potential root causes
Risk signalsAdmin/system-level operation
Attacks that exploit this kind of access
The rule that runs observability_metric_anomaly_detector safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For observability_metric_anomaly_detector, this is the rule to start with:
observability_metric_anomaly_detector is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every observability_metric_anomaly_detector call is checked against it from then on.
Questions about observability_metric_anomaly_detector
As a CTO, quickly identify anomalous cloud metrics (CPU, latency, memory) by comparing your infrastructure against AWS public benchmarks and CVE-linked hardware risks. Input your observed metrics (e.g., CPU utilization, request latency) and receive a risk assessment with potential root causes. Ideal for performance troubleshooting, security hardening, and capacity planning. Keywords: cloud observability, anomaly detection, CVE hardware risks, AWS benchmark comparison. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
observability_metric_anomaly_detector accepts 5 parameters: async, region, metricType, instanceType, observedValue. Required: metricType, observedValue. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for observability_metric_anomaly_detector: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Gapup Mcp. Nothing to install.
observability_metric_anomaly_detector is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the observability_metric_anomaly_detector rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for observability_metric_anomaly_detector. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
observability_metric_anomaly_detector is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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