Australian Towing Legality Check
Server Details
Legal towing check for ~46 AU vehicles — compliant/marginal/illegal + the binding constraint.
- Status
- Healthy
- Uptime
- 100.0% over 68 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2024-11-05
- URL
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusion between tools. The single tool's purpose is clearly defined.
With only one tool, naming consistency is not applicable, but the tool name 'check_towing' is clear and follows a verb_noun pattern.
The server has a single, highly specialized tool. While the count is low, it is appropriate for the narrow domain of Australian towing legality checks.
The tool covers the core query of towing legality for a vehicle and caravan combination. It includes checks for multiple constraints (braked capacity, towball download, GVM, GCM) and provides maximum ATM. Minor gaps like towing capacity without a caravan or general vehicle specs are not covered, but the domain is well-served.
Available Tools
1 toolcheck_towingAInspect
Use when someone asks whether an Australian vehicle can legally tow a particular caravan or trailer — "can my Ranger tow a 3 tonne van", "am I over GCM", "what is the heaviest caravan I can tow", "is my towing setup legal". Given a vehicle + variant and the caravan's ATM (plus optional tow-vehicle payload), returns whether the combination is legally compliant, marginal or illegal, WHICH limit binds (braked capacity, towball download, GVM or GCM — often not the braked rating everyone quotes), the maximum ATM that is legal for that vehicle, and remaining payload. Manufacturer-spec information, not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| load | No | people + gear in the tow vehicle (kg) | |
| van_atm | Yes | caravan Aggregate Trailer Mass (kg) | |
| variant | No | trim/variant, e.g. V6 or SR5 | |
| vehicle | Yes | make + model, e.g. Ford Ranger |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly explains what the tool returns (compliance status, binding limit, maximum ATM, remaining payload), notes that it uses manufacturer specifications (not advice), and describes the key outputs. It does not cover data freshness, rate limits, or required permissions, but for a query tool these are not critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that is information-dense but somewhat lengthy. It front-loads the use case and then lists outputs, but could be more concise by splitting into shorter sentences. Every sentence provides value, but the overall structure is not optimal for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description adequately explains return values (compliance status, binding limit, max ATM, remaining payload). It also clarifies the tool's scope (Australian vehicles, manufacturer specs, not advice). Minor missing details like data source update frequency prevent a perfect score, but it is largely complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% description coverage for all four parameters. The tool description adds little beyond repeating that 'load' is people+gear and 'variant' is trim. The description does not elaborate on how parameters interact or their defaults. Since schema coverage is high, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to check legal towing compliance for Australian vehicles with caravans/trailers. It provides specific example queries and outlines the outputs (compliance status, binding limit, max ATM, remaining payload). The verb 'check towing' and the resource (vehicle+caravan) are explicit, and the description distinguishes the tool from potential alternatives by specifying its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when to use the tool ('Use when someone asks whether...') and provides typical user queries. Although no alternative tools are mentioned (no siblings), the context is clear enough for an agent to decide when to invoke it. It does not include explicit when-not-to-use guidance but the use case is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
check_towing
Related MCP Connectors
US vehicle recalls, complaints, EPA figures, VIN decode and trouble codes, with sources.
UK MOT failure data and official UK, French, Japanese and EU vehicle recalls.
Indicative commercial rooftop solar assessments for Australian buildings, from open map data.
UK used cars: road tax (VED), ULEZ charges, MOT dates, DVSA reliability, live dealer stock.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to look up US NHTSA and EU Safety Gate car recalls and complaints, compare a model's years by risk score, check UK MOT failure rates, retrieve EU vehicle specifications with WLTP CO2 and fuel consumption, and verify Cyprus company records, EU VAT numbers via VIES and LEIs. It draws only on official open data and is hosted through Apify, so nothing needs to be installed.MIT
- AlicenseNot gradedqualityDmaintenanceProvides comprehensive vehicle reports by aggregating data from multiple public sources to decode VINs, check recalls, and view safety ratings. It enables users to validate VINs locally and retrieve technical specifications, fuel economy, and vehicle photos without requiring API keys.3 npmMIT
- AlicenseAqualityAmaintenanceOne-call Australian prudential data plumbing via APRA — cited responses for banking, superannuation and insurance context, not a data broker.681 PyPIMIT
- AlicenseAqualityAmaintenanceDecode VINs, look up specs, history, recalls, market value, and OBD codes. Recognize license plates and VINs from images. Access comprehensive vehicle data by year, make, and model to power automotive workflows.121MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.