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by airano-ir
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_system_metrics

Retrieve overall MCP server metrics including uptime, request counts, average response time, error rate, and requests per minute.

Instructions

Get overall MCP server metrics and statistics.

Returns system-wide metrics including:

  • Uptime

  • Total requests (success/failure)

  • Average response time

  • Error rate percentage

  • Requests per minute

Returns: JSON string with system metrics

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_system_metrics"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.13.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv3.4.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It lists returned metrics, which is helpful, but does not disclose any behavioral traits such as authentication requirements, idempotency, or potential errors. For a simple read-only tool, the description is acceptable but lacks explicit behavioral context.

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?

The description is concise with a clear first sentence. It uses a bulleted list for metrics, which is easy to read. However, it redundantly includes 'Returns:' twice, slightly reducing efficiency. Overall, it's well-structured and front-loaded.

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?

Given no parameters and the presence of an output schema, the description adequately explains the return format (JSON string) and lists the metrics. It does not mention side effects or permissions, but for a simple getter, it is reasonably complete.

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

Parameters4/5

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

There are no parameters, so schema coverage is 100%. The description adds no parameter info, but none is needed. Baseline for 0 parameters is 4, and the description meets this baseline as it does not need to compensate.

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

Purpose5/5

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

The description clearly states the tool gets overall MCP server metrics and statistics, listing specific metrics. It is distinct from sibling tools like get_system_uptime (focuses on uptime only) and get_project_metrics (project-level), so the purpose is well-defined and differentiated.

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?

The description implies usage for system-wide metrics but does not explicitly state when to use this tool over alternatives like get_project_metrics or get_system_uptime. No guidance on exclusions or context is provided, so the usage is only implied, not explicit.

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

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