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mcp-local-telemetry

mcp-local-telemetry

by Jamie643
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Get Top Processes

get_top_processes

Retrieve processes with high CPU usage to identify resource-heavy applications and troubleshoot local performance issues.

Instructions

Returns the N processes with the highest CPU usage.

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_top_processes"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many processes to return.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it only states the sort criterion. It doesn't say whether the result is a live snapshot or averaged, whether ties are broken deterministically, or whether privileges are required to see other users' processes.

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?

A single tight sentence with the ranking criterion front-loaded and no filler. It is efficient, though arguably too terse given the absence of annotations.

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

Completeness3/5

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

For a one-parameter read tool with no output schema, the core contract is covered. Still, ordering behavior and result format go unmentioned, leaving gaps that annotations would otherwise have filled.

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 limit parameter is fully documented in the schema, so the baseline is 3. The description's 'N processes' merely restates the limit parameter without adding format or behavior detail.

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?

The description states a specific verb (returns), resource (processes), and ranking criterion (highest CPU usage), which is enough to tell it apart from a metrics-aggregation sibling. It stops short of explicitly naming or contrasting with get_system_metrics, so sibling differentiation is only implied.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of the get_system_metrics alternative for aggregate CPU data. The agent must infer that this is for per-process inspection rather than system-level totals.

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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