MCP Tools
MCP Tools
- list_node_types_that_support_metrics: List node types supporting metrics retrieval
- list_available_metrics_for_node: List available metrics for a specific node
- get_metrics_for_node: Get metrics data for a resource using its node ID
- get_anomalies_for_metrics: Detect anomalies in metric data
Configuration
Configure the Metrics plugin by runninguv run unpage configure or by editing
the ~/.unpage/profiles/<profile_name>/config.yaml file:
Tools
The Metrics plugin provides the following tools to Agents and MCP Clients:list_node_types_that_support_metrics
List the types of nodes that support metrics retrieval.Arguments
NoneReturns
list[string]: Node types in the format “source:type” (e.g., “aws:ec2_instance”, “kubernetes:pod”) that support metrics collection.list_available_metrics_for_node
List the available metrics for a specific node.ArgumentsReturns
string
required
The unique identifier of the node to check for available metrics.
list[string] or string: List of available metric names for the node, or an error message if the node doesn’t support metrics.get_metrics_for_node
Get metrics data for a resource using its node ID.ArgumentsReturns
string
required
The unique identifier of the node to retrieve metrics for.
datetime
required
The starting time for the metrics range (ISO 8601 timestamp). A good starting point is one hour before the current time.
datetime
required
The ending time for the metrics range (ISO 8601 timestamp).
list[string]
List of specific metric names to retrieve. If not provided, all available metrics for the node will be returned. Can also be provided as a JSON string array.
list[dict] or string: Metric observations with timestamps and values, or an error/informational message.Note: Use list_available_metrics_for_node first to get valid metric names for the node.get_anomalies_for_metrics
Detect anomalies in metric data using statistical analysis.ArgumentsReturns
list[dict]
required
List of data points, where each entry contains a timestamp and value pair. Typically obtained from the results of
get_metrics_for_node.list[dict]: Detected anomalies in the metric data, including anomaly details and confidence scores.
