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sandraschi

Observability MCP Server

collect_performance_metrics

Collects system or service performance metrics, persists them for historical analysis, and enables trend detection.

Instructions

Collect comprehensive performance metrics for the system or specific service.

Uses OpenTelemetry for structured metrics collection and psutil for system monitoring. Metrics are persisted for historical analysis and trend detection.

Input Schema

NameRequiredDescriptionDefault
service_nameNoName of the service to monitor (default: system, max 50 chars)system

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It usefully discloses the mechanism (OpenTelemetry, psutil) and that results are persisted for historical analysis — a real side effect — but says nothing about cost, latency, permission requirements, or whether collection blocks or impacts the monitored service.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with the action front-loaded and no filler. The OpenTelemetry/psutil sentence is implementation detail that slightly exceeds what an agent needs for selection, but it is not wasteful enough to penalize further.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation, and the single parameter is fully specified. What remains thin is the side-effect/permission profile for a call that writes persisted metrics, but overall the description is sufficient to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is fully documented with its default and length limit. The description only echoes the 'system or specific service' distinction already expressed by the service_name default, so it adds little beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Collect ... performance metrics') plus the scope choice ('system or specific service'). It is distinguishable from neighbors like export_metrics and generate_performance_reports by implying in-place collection rather than export or reporting, but it never names a sibling to sharpen the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: you gather metrics when you want current performance data. There is no explicit statement of when to prefer this over monitor_system_resources, monitor_server_health, or export_metrics, and no prerequisites or exclusions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.