list_regionsCountries and their regions (German states, Austrian states, Swiss cantons, …) with codes, names and slugs accepted by the other tools.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It does not explicitly state that the tool is read-only or has no side effects, though the nature of a reference list implies safety. This lack of explicit transparency prevents a higher score.
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, compact sentence that conveys all essential information without any redundancy or filler.
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?
With no output schema, the description must explain the return content. It lists the key fields (codes, names, slugs) and scope (countries and regions), which is adequate for a simple listing tool. It does not specify the exact structure (e.g., array of objects), but this is not critical for basic usage.
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 tool has zero parameters, so the baseline of 4 applies. The description clearly explains what data is returned (countries, regions, codes, names, slugs), which covers the expected output without needing parameter documentation.
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 title clearly states 'List supported countries and regions', but the description itself is a noun phrase rather than an explicit verb phrase. Still, it conveys the purpose of enumerating reference data and is distinct from sibling tools.
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 phrase 'accepted by the other tools' implies that this tool provides valid values for use in other tools, giving clear context for when to invoke it. It does not explicitly state when not to use it, but the references to sibling tools provide sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools have mostly distinct roles: listing regions, retrieving holidays, and generating vacation plans. best_bridge_days and plan_vacation overlap somewhat in purpose, but their descriptions clarify that one returns the top six non-overlapping options while the other creates an optimal plan.
All tool names use lowercase snake_case, but they mix verb-led names (list_regions, plan_vacation), an adjective-led name (best_bridge_days), and a noun phrase (public_and_school_holidays). This is readable but not fully consistent in pattern.
Four tools is a tight, focused set for the vacation-planning domain. Each tool serves a clear purpose without unnecessary redundancy or bloat.
The set covers the core workflow: selecting a region, viewing holidays, and generating bridge-day or vacation plans. No significant missing operation is apparent for an informational planning API.