machship-mcp

Get Permanent Pickups for Company Location

machship_get_permanent_pickups

Read-onlyIdempotent

Retrieve all permanent scheduled pickups configured for a company location to manage recurring freight logistics.

Instructions

Gets all permanent scheduled pickups configured for a company location.

Args:

companyLocationId (number): Company location ID

Input Schema

Name	Required	Description	Default
`companyLocationId`	Yes	Company location ID

Output Schema

Name	Required	Description	Default
`errors`	No	Validation errors returned by Machship, if any
`object`	No	Response payload from the Machship API

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.0.1Nov 3, 2026

addedInput schema / properties / companyLocationId / maximum
```
Added value: +9007199254740991
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "properties": {
+    "errors": {
+      "anyOf": [
+        {
+          "items": {},
+          "type": "array"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "description": "Validation errors returned by Machship, if any"
+    },
+    "object": {
+      "description": "Response payload from the Machship API"
+    }
+  },
+  "type": "object"
+}

First observedv1.0.0Jun 12, 2026

TDQS

A3.9/5.0

Behavior3/5

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

The annotations already provide strong behavioral context, such as being read-only and idempotent. The description adds value by specifying that it retrieves *configured* schedules, which is useful domain context without being strictly necessary for safety.

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 highly concise, presenting the core function in a single sentence. The inclusion of the required Args block is structured and efficient, with no unnecessary padding.

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 the low complexity (1 parameter) and comprehensive annotations regarding safety, the description provides all necessary context for an AI agent to understand the tool's function and required inputs without further probing.

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% for a single parameter. The description provides the required label and meaning ('Company location ID'), meeting the minimum viable definition when the input structure is fully mapped by the schema.

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 action ('Gets'), the specific resource ('permanent scheduled pickups'), and the scope ('configured for a company location'). This makes it immediately identifiable as a retrieval tool focused on specific configurations.

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?

The description clearly defines what the tool retrieves. While it does not explicitly name the sibling tools (like 'add' or 'modify') that it is contrasted against, its singular focus on 'get' provides strong implicit guidance for when to use it.

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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