Common IANA timezone names for clock calls.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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?
No annotations are provided, so the description carries the full burden of disclosing behavior. It only states the content type (common names), not what the tool returns, whether it is read-only, or any edge cases; for a reference lookup this is a notable gap.
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 phrase with no redundant words, and the key content 'IANA timezone names' is front-loaded. It lacks a main verb, which slightly weakens the structure, but it is not padded.
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 and no annotations, the description should explain what the tool returns and how to invoke it; it does neither. The unrelated optional parameters and the lack of clarification about their relevance leave the agent without enough context to call the tool 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?
Schema description coverage is 100%, so each parameter (url, host, json, zone) is already documented by the schema. The description adds no extra parameter-level meaning and does not clarify why url, host, and json appear relevant to a timezone-name tool, but the high schema coverage keeps this at baseline.
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 identifies the resource (common IANA timezone names) and the intended use (clock calls), making it clear this is a reference list rather than a conversion or validation tool. It lacks an explicit verb like 'returns' or 'lists' and does not differentiate from sibling tools such as timezone or utc-time, 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'For clock calls' implies the tool should be used when supplying timezone names to clock-related operations, but there is no explicit when-to-use or when-not-to-use guidance. It does not name alternatives such as timezone or utc-time, leaving the routing decision to inference.
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.
Most tools have distinct outputs, but the URL-related tools (citation, normalize-url, domain-shape) and time-related tools (utc-time, timezone, iana-zones) form overlapping clusters that an agent could misselect. Descriptions clarify the differences, but the boundaries are not immediately obvious.
All names use lowercase hyphenation, but the set mixes imperative verb_noun names (inspect-robots, normalize-url, validate-json) with noun/adjective names (citation, compatibility, timezone, base64-ok). This is readable but not a consistent naming pattern.
Eleven tools is a reasonable size for a general-purpose utility server and none seem redundant enough to cut. A few could be consolidated, such as timezone and utc-time, but the count is not excessive.
The server covers several utility categories, including URL analysis, time, JSON validation, HTTP status, and base64, but has noticeable gaps such as no base64 decode, no timezone conversion, and no URL encoding/decoding. These missing operations limit what an agent can accomplish without another server.