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 full behavioral disclosure burden. It does disclose a meaningful behavior (dropping query and fragment), but it says nothing about input validation, error behavior, or what happens when the other accepted schema parameters (host, json, zone) are supplied, which is especially confusing given the mismatch between the description and the schema.
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 main purpose and immediately followed by the critical drop behavior. Every word earns its place; there is no fluff.
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 four schema parameters, no annotations, and no output schema, yet the description only addresses URL normalization. It does not specify the return structure or explain how the other parameters fit, so an agent cannot fully predict tool behavior across all valid inputs.
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 a baseline of 3 applies. The description adds useful behavior-level meaning for the url parameter, but it does not clarify how host, json, or zone relate to the stated behavior, leaving their purpose ambiguous beyond the schema descriptions.
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 clear operation ('Return origin, host, and path for a URL') and adds a precise behavioral detail (query and fragment are dropped). It is specific but does not explicitly distinguish itself from sibling tools like domain-shape or citation.
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 the tool should be used when a caller needs origin, host, or path rather than the full URL. However, it provides no explicit guidance on when to choose this tool over siblings, nor any exclusions or alternative routing.
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 operate on URLs (citation, compatibility, normalize-url, domain-shape, inspect-robots) and several on time (business-day, iana-zones, timezone, utc-time), creating some overlap in input types. The descriptions mostly clarify intent, but citation and compatibility in particular could still be confused.
Tool names mix nouns (citation, compatibility, timezone), verb phrases (inspect-robots, normalize-url, validate-json), and compound labels (business-day, iana-zones, utc-time). There is no consistent verb_noun or other naming pattern across the set.
Eleven tools is not excessive numerically, but the server name 'Weekday vs weekend' suggests a single narrow utility, while most tools are unrelated to that purpose. The set feels scattershot rather than deliberately scoped.
The tools span URL inspection, time/date, and JSON validation without a unifying domain, so there is no coherent capability surface to complete. Each mini-cluster has gaps, such as URL tools that only inspect and time tools that lack conversions or date arithmetic.