Split a hostname into labels without WHOIS or ownership data.
| 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?
With no annotations present, the description must carry the behavioral disclosure burden, but it only states the core split operation and one negative guarantee. It does not disclose how a URL vs hostname is treated, what the output structure is, whether any network access occurs, or how invalid or empty input is handled, so an agent cannot predict runtime behavior.
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?
A single front-loaded sentence states the operation first and then the exclusion; every word earns its place. There is no 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?
For a tool with no output schema and no annotations, the description is too thin: it omits the result format, the expected input parameter, and error semantics. An agent would not be able to confidently construct a correct call or interpret the response from this definition alone.
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?
Input-schema coverage is 100%, so the baseline is 3: each parameter has a description. The tool description adds no parameter-specific guidance, and because all four parameters are optional, it is not obvious whether to pass host, url, or ignore json/zone; the description's 'hostname' maps most naturally to the host parameter.
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 uses a specific verb and resource ('Split a hostname into labels') and immediately scopes the tool with 'without WHOIS or ownership data,' making its intent unmistakable. This also distinguishes it from siblings like normalize-url, which normalizes rather than splits, and from any ownership-lookup tool.
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 purpose implies the usage context: use this when you need hostname labels, not WHOIS or ownership data. However, it never explicitly names alternatives or states when this tool should be preferred over siblings such as normalize-url or citation, so the guidance is mostly implied rather than direct.
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.
Tools cluster into URL/HTTP and time-related groups, but within each cluster the purposes are mostly distinguishable. citation, normalize-url, and domain-shape all touch hostnames, while timezone, utc-time, and weekday-utc all return current time data, so an agent could briefly hesitate when selecting among them.
All names use lowercase hyphens, but there is no consistent verb_noun or noun pattern. Some tools use verb-object naming like inspect-robots and normalize-url, while others are plain nouns like citation, timezone, and status-catalog, making the set feel inconsistent.
Eleven tools is a reasonable count for a utility server and does not feel bloated. However, the selection spans many unrelated concerns—URL parsing, time, JSON validation, robots.txt, HTTP status—so the set feels broader than a single focused purpose.
For a privacy-focused URL/HTTP utility set, there are notable gaps such as no redirect or header inspection, and for time utilities there is no timezone conversion tool. The surface covers basic atomic operations but lacks the cohesive lifecycle or workflow coverage that would make it feel complete.