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Factory Intelligence MCP Server

Factory Intelligence MCP Server

by lvshrd
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_productivity_kpi

Compute productivity metrics for a specified start and end time to evaluate factory performance.

Instructions

Computes productivity metrics for a given time range.

Args:
    start_time: ISO 8601 string (e.g., '2025-12-01T00:00:00Z')
    end_time: ISO 8601 string (e.g., '2025-12-07T23:59:59Z')

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "start_time": "<start_time>",
      "end_time": "<end_time>"
    },
    "name": "get_productivity_kpi"
  }
}

Input Schema

NameRequiredDescriptionDefault
end_timeYes
start_timeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations and the description does not disclose any behavioral traits such as read-only, auth needs, or rate limits. The description only states the tool computes metrics, which is insufficient for a tool with no annotations.

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?

Concise docstring-style description with parameter list. Could be more front-loaded, but no superfluous content.

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?

The output schema exists, so return values are covered. However, the description lacks details on what 'productivity metrics' includes and any limitations on the time range.

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?

Although schema coverage is 0%, the description provides ISO 8601 format examples for start_time and end_time, adding meaningful guidance beyond the schema's bare 'string' type.

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 it computes productivity metrics for a time range, distinguishing it from sibling tools like get_downtime_kpi or get_quality_kpi.

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?

No guidance on when to use this tool vs alternatives like get_downtime_kpi, or what constraints apply (e.g., maximum time range).

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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