Short catalog of common HTTP status codes.
| 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 behavioral disclosure, and it discloses nothing beyond a vague topic. It does not explain how the four input parameters are consumed, whether the tool mutates anything, what it returns, or what side effects exist — a serious gap for a tool with zero annotation coverage.
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 short sentence with no redundancy, and the main idea is front-loaded. But it is under-specified rather than efficiently complete — brevity here comes at the cost of omitting any operational detail.
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 four parameters that appear unrelated to the description, no annotations, no output schema, and no explanation of behavior or return value, the definition is far from complete. An agent has almost no information needed to invoke this tool correctly, and the topic/schema mismatch actively increases confusion.
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 is already documented in the input schema, earning the baseline of 3. However, the description itself adds no value about the parameters and fails to bridge the gap between the 'status codes' framing and the url/host/json/zone inputs.
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 names a resource ('common HTTP status codes') but never states the operation — does it list, look up, explain, or map them? The resource also conflicts with the input schema, which contains url, host, json, and zone parameters that have no obvious relationship to HTTP status codes. This leaves an agent unable to tell what the tool actually does.
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?
There is no guidance on when to use this tool versus any alternative, and no sibling tool is mentioned. Worse, the description is potentially misleading because the stated topic (HTTP status codes) does not align with the parameters, so an agent cannot infer appropriate usage conditions.
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 timezone tools overlap heavily: `timezone` already supports named IANA zones, making `utc-time` and `tz-america-new-york` largely redundant. The URL tools also blur together (`citation` vs `normalize-url` both return host/scheme information), and `compatibility` is too vague to confidently distinguish from the other request-classification tools.
All names share a lowercase hyphenated style, but they mix conventions: verb-prefixed tools like `inspect-robots`, `normalize-url`, and `validate-json` sit alongside noun phrases like `domain-shape`, `status-catalog`, and `utc-time`, plus single-word names like `timezone` and `citation`. The names are readable and predictable in format, but not in action pattern.
Eleven tools is not an extreme number, but the set is not well-scoped: it mixes time, URL normalization, HTTP status, robots.txt, and JSON validation concerns. The count feels like several small toolkits merged into one server rather than a focused tool collection where each tool clearly earns its place.
There is no coherent domain to call complete. As a clock server, it lacks timezone conversion, offsets, or date formatting; as a web utility server, it lacks common operations like fetching content or inspecting headers. Significant operations for either inferred purpose are missing, so agents would likely hit dead ends.