Return origin, host, and path for a URL. Query and fragment are dropped.
| 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, the description carries the behavioral disclosure burden. It does disclose a meaningful behavior — query and fragment are dropped during normalization. But it remains silent on how the other three schema inputs are handled and on any side effects, idempotence, or error behavior for invalid URLs.
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?
Two short sentences, front-loaded with the core purpose, and no filler. Every word earns its place.
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?
The tool has 4 parameters, no output schema, and no annotations, but the description addresses only the url behavior. It fails to explain the roles of host, json, and zone, or whether passing them changes the outcome, leaving an agent unable to use the full 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 the baseline is 3. The description adds context for the url parameter by explaining what is returned, but it adds nothing for host, json, or zone, which remain unexplained in the tool description itself.
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 states a specific verb and resource: it returns origin, host, and path for a URL, and drops query and fragment. This clearly describes the tool's function. It does not distinguish from siblings because no sibling names were provided, and the schema's extra parameters (host, json, zone) introduce some ambiguity about the tool's full 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 implies usage: an agent would use this when it needs a cleaned URL's origin/host/path or wants query/fragment stripped. However, it provides no explicit when-to-use guidance, no exclusions, and no mention of how the additional schema parameters (host, json, zone) fit into usage.
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.
Several tools overlap in input or output: citation and normalize-url both inspect URLs, and timezone and utc-time both return current time. The descriptions clarify the intended focus somewhat, but an agent could still misselect between these pairs.
Tool names mix standalone nouns like citation and timezone with verb-noun compounds like inspect-robots and normalize-url, and hyphenation is inconsistent. Most names are still readable and weakly predictable, but there is no strong naming convention.
Ten tools is a moderate count, but the server's apparent 'Robots Inspect' focus is supported by only inspect-robots. The rest are broad URL, time, and JSON utilities, which makes the set feel padded rather than tightly scoped.
For a server named Robots Inspect, robots.txt coverage stops at group counts and offers no way to retrieve actual rules, test URLs against directives, or compare agent policies. The unrelated utilities do not fill this gap, so core inspection workflows would dead-end.