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Anandb71

CargoMind MCP Server

by Anandb71
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

track_shipment

Get current shipment status, location, ETA versus promised delivery, carrier, vehicle, and recent events by shipment or order ID.

Instructions

Track a shipment: current status, location, ETA vs promised delivery, carrier, vehicle and recent events.

Use this first whenever the user mentions a specific shipment or order.

Args:
    shipment_id: Shipment ID such as "SHP-1001" (also accepts "shp1001" or "1001").

Returns:
    The shipment (status, priority, origin_city, destination_city, last_city, eta, promised_by,
    is_late, delay_hours, hours_to_promise, carrier_name, vehicle, customer, weight_kg, notes)
    plus ``recent_events`` (latest 5, newest last). On a miss: status="error" with suggestions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
shipment_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations exist, so the description carries the full load, and it does disclose real behavior: accepted ID variants ('SHP-1001', 'shp1001', '1001'), that recent_events returns only the latest 5 newest-last, and the miss behavior (status="error" with suggestions). It omits auth/permission needs and rate limits, which keeps it from a 5.

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?

Front-loaded with the purpose and usage trigger before the Args/Returns blocks, and every sentence carries information. The Returns block restating 15 output fields is somewhat redundant given an output schema exists, mildly diluting conciseness.

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?

For a single-parameter read tool with an output schema, the description supplies the identifier format, the priority trigger, and error behavior. It is essentially complete, with only minor gaps around permissions and any pagination/limit nuance for recent_events.

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

Parameters5/5

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

Schema description coverage is 0%, so the schema provides no parameter meaning at all. The description compensates fully for the single parameter by giving a concrete example ID and documenting that normalized/short forms are also accepted, which is information an agent could not get from 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 ('Track a shipment') and enumerates the exact facets returned: status, location, ETA vs promised delivery, carrier, vehicle, recent events. It implicitly separates itself from list_shipments via 'a specific shipment or order' but never names a sibling, so it stops short of a 5.

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

Usage Guidelines4/5

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

'Use this first whenever the user mentions a specific shipment or order' is an explicit trigger condition with a priority ordering relative to other tools. It gives no when-not guidance or named alternative (e.g. list_shipments for broad queries), so it is clear context without exclusions.

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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